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Using the social constructivist perspective of learning, this study aims to examine the patterns and the key areas of entrepreneurial learning based on a case study of 16 participants who were the incubatees of two technology-based business incubators in China. The key research question is: how do novice entrepreneurs, focusing on technology-based business incubators, learn from a social constructivist perspective?

The researchers applied a qualitative methodology in this study as they wanted to understand better the complexity of the learning process that is hard to achieve quantitatively. The qualitative data was collected through in-depth interviews with the incubatees, who were the managers and owners of their businesses. The interviews with the entrepreneurs were mainly focused on the learning patterns and the factors influencing learning through the use of the critical incident technique.

This will allow incubator managers to better evaluate the extent of effective entrepreneurial learning within the incubator's eco-system. The results show that the participants learn through socially constructivist systems that are structured around the support provided by the incubators. Learning in this context takes place in an extended spectrum, and participants are more interested in learning from networking with experienced entrepreneurs rather than from other incubatees or formal courses. Findings of this study help incubator managers and novice entrepreneurs to better shape learning and teamwork in an effort to improve the learning process. Policy makers should consider introducing schemes that encourage novice entrepreneurs to exhibit the creativity and innovation behaviour reported by experienced entrepreneurs.

The focus of this study is primarily on incubators as the context of learning, whereas the macro-environmental factors, such as the socio-cultural and regulatory environments in China, were considered as playing a subtle role and would affect the incubatees' learning indirectly. The paper is based on a relatively small sample size and is geographically located in Ningbo, China. As such, the authors call for further research for comparative studies with a larger sample size so that a possible theory of entrepreneurial learning in the context of incubators might emerge in the future.

This study aims to examine whether auditors who specialize in research and development (R&D) activities help reduce managers’ opportunistic adjustment of R&D expenditure for real earnings management (REM).

Using a sample of US firms during the 2001–2017 period, the authors identify auditors’ R&D specialization as their prior experience of auditing R&D expenses spent by each client’s peers. The authors measure R&D-based REM as the negative deviation from the predicted level of R&D expenditure.

The authors find that clients of R&D specialist auditors are less likely to engage in REM through a discretionary reduction of R&D expenditure. This effect is more pronounced when clients face higher competition, have larger investment opportunities and entail higher audit risks.

This study shows that auditors’ specialized knowledge can facilitate stronger monitoring of clients’ real decisions, providing implications for auditors’ knowledge acquisition and transfer in specific types of transactions.

This study contributes to the literature by documenting the governance role played by R&D specialist auditors in clients’ real economic decisions. Moreover, the study identifies R&D as a distinct area of auditor specialization.

Social participation and user-generated contents have engendered an era when “any receiver can be a provider.” Although studies have emphasized on increasing the number of subscribers conducive to platform success, the issue regarding why viewers drop their registered YouTuber channels has been less addressed. This article aims to present and empirically test a causal model to account for the pattern of discontinuous intention of attention to YouTuber channels.

Inspired by the expectation–disconfirmation theory, the study proposes and examines a research model by using an empirical quantitative approach. The proposed model considers channel and YouTuber facets, as well as potential moderation effects of viewing seniority.

Analysis of a sample of 406 questionnaires revealed that ads interference is not a significant reason for discontinuation of viewing a channel, in contrast to insufficient playfulness and inconsistency. Regarding YouTubers’ features, both interaction inadequacy and negative self-disclosure are significant determinants of perceived dissatisfaction and discontinuation of viewing. The effects of determinants of discontinuity depend on viewers' seniorities, except for negative self-disclosure.

While existing studies have focused mainly on revealing the determinants associated with the behavioral intention of viewing YouTuber channels to increase self-media performance, this research contributes insights into the literature investigating why existing viewers stop following a certain YouTuber channel. From a psychological perspective, this study demonstrates the value of modeling discontinuous behaviors toward YouTuber channels in the domain of social marketing.

This paper aims to examine the association between the perceived values of information (economic, hedonic, functional, psychological) and the actual use of social networking channels (Instagram/Facebook groups/SNS personal profiles or messaging) for seeking information on accommodations.

879 respondents aged 18–55, who travel abroad as individual tourists at least once a year and are responsible for their own accommodation choice, were surveyed.

The study shows that all the values of information are more likely to be provided through posting a question on one's profile/messaging options (i.e. friends and relatives), than through Facebook groups and Instagram. The multivariate findings show that different values are associated with different SNS channel choices for seeking information.

The study provides an innovative approach to the motivations behind the use of different SNS platforms for travel information search by consumers. It offers practical implications, suggesting how to provide the relevant content on each channel.

Climate change has led to a rise in the frequency, intensity and scope of droughts, posing significant implications for businesses. This study examines the impact of local community drought levels on audit pricing. Additionally, it explores the moderating effects of high-tech industries, auditor busyness and the level of local community concern regarding the drought crisis.

This study employs a mixed-methods approach to rigorously test the research hypotheses. The quantitative phase of the study utilizes a sample of 1,278 firm-year observations from Iran’s capital market. For the analysis of the quantitative data, ordinary least squares regression with clustered robust standard errors is used. Additionally, this research supplements its quantitative findings with qualitative evidence obtained through semi-structured interviews with 19 Iranian audit partners.

The results suggest that firms operating in provinces facing severe droughts experience notably higher audit fees. Furthermore, the positive relationship between drought and audit fees is weakened when auditors are busy, local community concern regarding the drought crisis is high or the firm operates within high-tech industries. These findings are supported by a range of robustness checks and qualitative evidence gathered from the field.

This research contributes to the growing literature on climate change by examining the influence of local community drought levels on audit pricing within an Iranian context. Additionally, our study sheds light on how high-tech industries, auditor workload and the level of local community concern regarding the drought crisis moderate the relationship between drought and audit fees. Importantly, our study pioneers in providing mixed-methods evidence of the association between drought severity and audit fees.

Problems such as information asymmetry and a lack of trust among construction practitioners damage the quality and progress of construction projects. The decentralization, transparency, traceability and temper-proof nature of blockchain technology (BCT) can provide solutions and facilitate multiparty cooperation. However, BCT acceptance in the construction industry is relatively low, and there are few pilot projects adopting BCT. Most relevant literature focuses on BCT acceptance at the industry and organizational levels, but the impact of non-managerial practitioners executing BCT or the traditional approach in day-to-day work tends to be disregarded. This study aims to establish a theoretical model of BCT acceptance, identify key influencing factors and paths of behavioral intention to adopt BCT and promote strategies to enhance BCT adoption.

A new BCT acceptance model for construction practitioners was proposed. A survey was performed with 203 construction practitioners in Shenzhen, China and post-survey interviews were conducted with four BCT experts for validation. Covariance-based structural equation modeling was used to examine the influence paths and moderating effect analysis was performed to check practitioners’ differential perceptions.

Performance expectancy, social influence, facilitating conditions and perceived behavioral control significantly and positively influence behavioral intention to accept BCT, while impacts from effort performance and risk are negative. Overcoming obstacles related to the effort required for BCT adoption and effective risk management will be essential to unlocking BCT’s transformative potential. Then, the moderating effects of respondents’ gender, degree and BCT knowledge as well as the project type involved were analyzed. Continued adoption of BCT in the construction industry has the potential to revolutionize project management, transparency and trust among stakeholders.

The findings of this research can help practitioners and government agencies understand crucial influencing factors and pathways of BCT acceptance. Targeted measures, such as increasing practitioners’ benefits and sense of BCT usefulness, conducting pilot projects and increasing publicity, were proposed for project leadership teams to enhance BCT adoption. This may lead to increased efficiency, reduced disputes and more streamlined and secure construction processes, ultimately enhancing the industry’s overall performance.

Few studies have explored BCT acceptance from the perspective of non-managerial construction practitioners. The BCT acceptance model proposed in this study is a novel adaptation of previous technology acceptance models, with new factors (risk and perceived behavioral control) and moderating variables (degree, BCT knowledge and project type) added for better understanding of non-managerial practitioners’ perceptions and differences.

Key performance indicators (KPIs) play a pivotal role in evaluating the level of success of an organization in achieving its business objectives. The objective of the current research is to identify and prioritize effective KPIs in branding products and construction projects, which contribute to the success of construction companies in a competitive environment.

The present research is of an inferential, descriptive and survey nature. In this study, we identified the influential key performance indicators of construction companies in branding products and construction projects for success in a competitive environment through a literature review and expert opinions. The data were collected using a questionnaire, and a combination of the one-sample t-test method with a 95% confidence level and the fuzzy multiple attribute decision-making (FMADM) method was employed for analysis.

The results indicate that the most influential key performance indicators for construction companies in branding products and construction projects for success in a competitive environment are, in order of significance, the following indices: “Marketing and Advertising,” “Financial,” “Creativity,” “Technical and Operational” and “Social and Political.”

The present research examines the importance of branding construction products and projects for the success of construction companies by improving their business objectives and utilizing key performance indicators throughout the product lifecycle (production and construction). This study provides solutions on how construction companies can increase their competitive advantage through branding and achieve long-term success in the global construction industry.

Construction professionals are the major contributors to developing a sustainable construction industry, whereas architects, engineers and quantity surveyors are the key construction professionals who must play extraordinary roles in achieving better sustainable construction. Therefore, this study aims to identify the job attributes of key Sri Lankan construction professionals in addressing challenges associated with climate change.

The study adopted a mixed research approach. A literature review and preliminary semi-structured interviews were used to appraise the job roles of architects, engineers and quantity surveyors in addressing challenges associated with climate change. The data collected through the qualitative approach were used in an online questionnaire survey, and the findings were analysed using the relative index method.

The findings highlight that regardless of the knowledge of the professional category on green rating tools, carbon footprint, adaptation of renewable energies for the reduction of energy consumption, building information modelling-related applications and waste management concepts/practices are the foremost job attributes required for the key Sri Lankan construction professionals in addressing challenges associated with climate change.

The results from this study provide a handful of guidance to construction industry professionals, national and international professional institutions, non-governmental organisations and other relevant authorities to address climate change within the built environment by identifying ways for improving the relevant key job attributes of construction industry professionals.

To the best of the authors’ knowledge, this is the first study that explores the job attributes of key Sri Lankan construction professionals in addressing the challenges associated with climate change.

Construction sustainability (CS) is a strategic reaction to the sustainability expectations of the construction industry's external stakeholders. The extant literature has viewed the environmental, social and economic dimensions of CS as having independent effects on financial performance. Due to the influence of common stakeholders, however, interactions in these dimensions will be present in their effect on financial performance. Accordingly, this study identifies the mechanisms of the interactions between the three CS dimensions and how they jointly affect financial performance.

Content analysis of GRI reports of 60 large construction organisations, followed by a hierarchical regression analysis was used to identify the interactions between environmental, social and economic CS in their effect on financial performance.

Economic CS was found to indirectly, and not directly, affect financial performance, the effect being mediated by both environmental and social CS. Environmental CS was found to have a strong negative effect on financial performance, whilst social CS was found to have a strongly significant positive effect on financial performance.

The motivation for engaging in CS is that investment in economic CS will have a positive effect on both environmental and social CS outcomes, which, in turn can have a combined effect on financial performance.

This is one of the first studies investigating the effect of interactions between the environmental, social and economic CS dimensions on the financial performance of construction organisations. It is also one of the first studies that applies a sociotechnical framework to this relationship.

The purpose of this paper is to propose a scenario-based grey methodology using clustering and optimizing with imprecise and uncertain body size data in an emergency assembly point area to assign the people on a campus to reach the emergency assembly points under uncertain disaster times.

Grey clustering and a new grey p-median linear programming model are developed to determine which units to assign to the pre-determined assembly points for a main campus in case of a disaster. The models have two scenarios: 70 and 100% occurrence capacities of administrative and academic personnel and students.

In this study, the academic and administrative units have been assigned to determine five different emergency assembly points on the main campus by using the numbers of the academic and administrative personnel and student and distances of the units to the assembly point areas of each other. The alternative solutions are obtained effectively by evaluating capacity utilization rates in the scenarios.

It is often unclear when disasters can occur and therefore, a preliminary preparation time must be required to minimize the risk. In the case of natural, man-made (unnatural) or technological disasters, the people are required to defend themselves and move away from the disaster area as soon as possible in a proper direction. The proposed assignment model yields a final solution that effectively eliminates uncertainty regarding the selection of emergency assembly points for administrative and academic staff as well as students, in the event of disasters.

Grey clustering suggests an assignment plan and concurrently, an investigation is underway utilizing the grey p-median linear programming model. This investigation aims to optimize various scenarios and body sizes concerning emergency assembly areas. All campus users who are present at the disaster in units of the campus are getting uncertainty about which emergency assembly point to use, and with this study, the vital risks aim to be ultimately reduced with reasonable plans.