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The study explores how the intention to export affects financing and non-financing variables for small and medium-sized enterprises (SMEs) in a low-income country (LIC). The objectives of this study are (1) to discern between regional and global exporting and (2) to evaluate its policymaking implications.

Primary survey data were collected from 330 Rwandan SMEs and were analysed using ordered logistic models as an application of the expectation-maximisation iterating algorithm, which was tested for robustness using a sampling model variation.

The results show that alternative sources of finance are the predominant choice to finance the intention to export within and outside Africa. As the scope of export intentions broadened from regional to global, there was a shift in preferences from less formal to more formal lending technologies, moving from methods like factoring to lines of credit. Moreover, reliance on bank officers became more significant, with increasing marginal effects. Finally, the study determined that government financing schemes were not relevant for SMEs pursuing either regional or global exporting.

Whilst alternative sources of finance predominate the export intentions of Rwandan SMEs, establishing a robust banking relationship becomes crucial for global exporting. Despite this implication, the intention to export should prompt more transparent communication regarding government financial support programmes. There is an opportunity for increased usage of relationship lending to customise support for SMEs involved in exporting, benefiting both the private and public sectors.

This study accentuates how export distance alters SME financing priorities. The results also contribute to understanding how the value of relationship lending changes when less familiar markets (i.e. global exporting) are the objective. Moreover, the study offers a new perspective on how institutional voids affect entrepreneurial financing decisions in LICs.

The purpose of this study was to analyze the effects of social media analytics on firm performance using a sample of small and medium enterprises (SMEs) in Thailand. This study also investigated whether entrepreneurial orientation (EO) moderated the effects of social media analytics on firm performance.

This study used SMEs listed in the Department of Business Development of Thailand as the sampling frame. Probability sampling was used to draw the sample. A questionnaire survey was used to collect data from 334 firms. The data were analyzed using partial least squares structural equation modeling.

The results supported the positive association between social media analytics practices on firm performance. Moreover, this study found that EO moderated this association significantly. In particular, the positive association between social media analytics practices on firm performance was higher for firms that exhibit a high EO than those that exhibit a low EO. This result indicated that firms that implement social media analytics practices achieved higher performance when they exhibited a high EO.

Social media data analytics should be implemented to strengthen the technological competence of firms. Moreover, firms should integrate EO practices into their implementation of social media analytics to increase their ability to generate substantial improvements in their strategic implementation, thereby enabling them to gain sustainable competitiveness in their market.

Because SMEs are the driving force for economic growth and development in Thailand, their ability to achieve higher performance when they effectively integrate EO practices into their implementation of social media data analytics could be beneficial for the sustainable development of Thailand, especially in the current data-driven era.

The result that EO moderates the effect in enhancing social media analytics practices’ influence on firm performance provides new knowledge that extends the boundary of research on this topic. The authors provided a theoretical explanation to clarify the way the implementation of social media analytics practices should be integrated with EO to increase the level of performance that firms achieve from such practices.

This study aims to examine the relationship between internal and external factors and job satisfaction, and between job satisfaction and auditors’ performance.

This research used deductive approach. Data was gathered from 83 auditors in the Saudi Organisation for Certified Public Accountants (SOCPA) database. By implementing the partial least squares-structural equation modelling (PLS-SEM) technique, the suggested hypotheses were examined.

The results show that internal factors, i.e., achievement, advancement, recognition and growth, significantly impact job satisfaction. Subsequently, the external factors, i.e., company policies, relationship with a peer and relationship with supervisor, significantly impact job satisfaction. In contrast, work security has no relationship with job satisfaction. Furthermore, job satisfaction is a significant driver for auditors' performance.

This research sheds light on the relationships between internal and external factors, job satisfaction and auditors' performance in the Saudi context. It would be interesting to investigate these relationships in a different setting, such as a different country, time or industry. Future studies should broaden the sample frame to include different types of employees to obtain more generalisable results.

This study may help managers of auditing departments formulate appropriate strategies and design effective programs to increase the level of job satisfaction between auditors by enhancing such factors, which will lead to improving the auditors' performance.

This research provide an empirical evidence to support the theoretical assumptions of Herzberg's which is much needed.

The purpose of this paper is to use Bourdieu’s Theory of Capital–Field–Habitus to explore how refugees, asylum seekers and migrants accumulate and mobilise social, cultural, symbolic and economic capital to find meaningful work in the Australian construction industry.

The paper reports the results of a survey of refugees, asylum seekers and migrants who have either successfully or unsuccessfully searched for employment in the Australian construction industry.

The findings dispel widely held negative stereotypes of about this group by describing a highly capable workforce which could address significant skills shortages in the industry, while concurrently diversifying the workforce. However, it is found that refugees, asylum seekers and migrants face considerable barriers to finding meaningful employment in the construction industry. In circumventing these barriers, education institutions, charities and community-based organisations play an especially important role, alongside friends and family networks. They do this by helping refugees, asylum seekers and migrants accumulate and deploy the necessary capital to secure meaningful work in the construction industry. Disappointingly, it is also found that the construction industry does little to help facilitate capital accumulation and deployment for this group, despite the urgent need to address diversity and critical skills shortages.

Employing Pierre Bourdieu’s Theory of Capital–Field–Habitus, the findings make a number of new theoretical and practical contributions to the limited body of international research relating to the employment of refugees, asylum seekers and migrant workers in the construction. The results are important because meaningful employment is widely accepted to be the single most factor in the successful integration of refugees, asylum seekers and migrants into a host society and the construction industry represents an important source of potential employment for them.

This study explores the determinants of police officer support for pre-arrest/booking deflection programs that divert people presenting with substance use and/or mental health disorder symptoms out of the criminal justice system and connect them to supportive services.

This study analyzes responses from 254 surveys fielded to police officers in Delaware. Questionnaires asked about views on leadership, approaches toward crime, training, occupational experience and officer’s personal characteristics. The study applies a new machine learning method called kernel-based regularized least squares (KRLS) for non-linearities and interactions among independent variables. Estimates from a KRLS model are compared with those from an ordinary least square regression (OLS) model.

Support for diversion is positively associated with leadership endorsing diversion and thinking of new ways to solve problems. Tough-on-crime attitudes diminish programmatic support. Tenure becomes less predictive of police attitudes in the KRLS model, suggesting interactions with other factors. The KRLS model explains a larger proportion of the variance in officer attitudes than the traditional OLS model.

The study demonstrates the usefulness of the KRLS method for practitioners and scholars seeking to illuminate patterns in police attitudes. It further underscores the importance of agency leadership in legitimizing deflection as a pathway to addressing behavioral health challenges in communities.

This study is based on the regulatory focus theory and conservation of resources theory to examine how information confusion leads to users’ discontinuous usage intention of social networking sites (SNSs), with the mediating mechanisms of users’ motivation and affectivity.

Data were obtained from 270 users in different SNSs in Vietnam. Structural equation modeling was used to analyze the sample data and test the hypotheses.

Results show that information confusion has a positive influence on discontinuous usage intention, and prevention focus positively mediates this relationship. Furthermore, the negative affectivity positively mediates the link between information confusion and discontinuous usage intention and that between prevention focus and discontinuous usage intention. In addition, prevention focus and negative affectivity together play a serial mediating effect in the link between information confusion and discontinuous usage intention.

This study extends the regulatory focus theory and conservation of resources theory to validate a model that explains the transitional process of users’ motivation and affectivity in the link between information confusion and discontinuous usage intention of SNSs. The findings of this study provide implications for academic researchers and business managers of SNSs to understand and make better decisions to retain their users.

This study considers the “technology creation” characteristic of technical knowledge-intensive business services (T-KIBS) and examines how human capital and intellectual property rights (IPR) protection affect the location choice of foreign direct investment (FDI) in China for two types of T-KIBS: (1) information transmission, software and information technology (ICT) services and (2) scientific research and technology (SCI) services.

Our empirical analysis is based on panel data on 22 Chinese provinces from 2009 to 2017. We use the generalized method of moments estimation for the regression analysis.

FDI in ICT services prefers regions with high human capital, while FDI in SCI services favors regions with good IPR protection.

Future research could use more comprehensive data and qualitative interviews to enhance the findings.

These findings provide a foundation for China’s future policy on attracting FDI into T-KIBS, especially in areas related to human capital and IPR protection.

This study bridges the research gap on the FDI location choice of T-KIBS in China by clarifying the influences of human capital and IPR protection and providing theoretical support for the location choice of T-KIBS FDI.

The number of young people using e-cigarettes (commonly referred to as vaping) has grown at an alarming rate, creating the need for urgent action. This paper demonstrates rapid step-by-step iterative application of the Co-create, Build and Engage (CBE) framework to showcase how marketing was applied in response to emerging trends that have negative health and environmental consequences. This paper aims to demonstrate how CBE is applied iteratively, ensuring student feedback leads module development.

In Study 1, a pure seven-step co-design implementation, 19 high school students were invited to co-design a vaping prevention approach that would work for them and other people like them. During the sensitisation phase of co-design, students completed one Blurred Minds Vaping module. Feedback grids were provided, with students identifying likes, dislikes and ideas. This likeability data was used, together with input from technical experts and pedagogical best practice, in a 12-week research and development project that aimed to develop a new online learning module focused on vaping and their environmental impacts for the Blurred Minds Academy. The new module was tested with 20 high school students. Feedback grids were provided once again, allowing a comparison of results.

Examination of feedback grid data demonstrates that the newly developed Vaping and the Environment module was improved. Considerations taken on board in the new module design (e.g. increased variability within the module) overcame criticisms expressed previously (e.g. it was boring and too long). Other criticisms remained evident, albeit at a much lower proportion suggesting the new Vaping and the Environment module, and future Blurred Minds module development, would benefit from iterative CBE application.

Conduit et al. (2022) note that marketing academia has been criticised for having an increasingly less relevant managerial agenda. This paper outlines a rapid step-by-step application of marketing in response to one of society’s most pressing health challenges – vaping. The iterative application of CBE is outlined, demonstrating that the student experience can be enhanced when marketing’s continual improvement mindset is used. This is the first vaping prevention programme that has included substantive information around the negative impacts of vaping on the environment.

This study aims to investigate whether social reputation via corporate social responsibility (CSR) awarding facilitates access to debt and decreases the cost of debt and whether governance mechanisms moderate this relationship.

The sample covers the period between 2002 and 2021, during which CSR award data were available in the Thomson Reuters Eikon/Refinitiv database. The empirical models are based on country, industry and year fixed-effects regression.

While the main findings produced an insignificant result for access to debt, they indicated strong evidence for the positive relationship between CSR awarding and the cost of debt. Moreover, the moderating effect highlights that while the sustainability committee helps CSR-awarded companies access debt more easily, independent directors help firms decrease the cost of debt via CSR awarding. Furthermore, the results differ between the US and the non-US samples, earlier and recent periods, high- and low-leverage firms and large and small firms.

For the first time, to the best of the authors’ knowledge, the authors assess whether social reputation via CSR awarding facilitates access to debt and decreases the cost of debt in an international and cross-industry sample. Little is known about the effect of social reputation on loan contracting, although social reputation conveys broader information that goes beyond the firm’s internal (performance) and external (reporting) CSR practices. The authors also draw attention to the differing roles of distinct governance mechanisms in leveraging social reputation for loan contracting.

Ensuring the safety of structures is important. However, when a structure possesses both an implicit performance function and an extremely small failure probability, traditional methods struggle to conduct a reliability analysis. Therefore, this paper proposes a reliability analysis method aimed at enhancing the efficiency of rare event analysis, using the widely recognized Relevant Vector Machine (RVM).

Drawing from the principles of importance sampling (IS), this paper employs Harris Hawks Optimization (HHO) to ascertain the optimal design point. This approach not only guarantees precision but also facilitates the RVM in approximating the limit state surface. When the U learning function, designed for Kriging, is applied to RVM, it results in sample clustering in the design of experiment (DoE). Therefore, this paper proposes a FU learning function, which is more suitable for RVM.

Three numerical examples and two engineering problem demonstrate the effectiveness of the proposed method.

By employing the HHO algorithm, this paper innovatively applies RVM in IS reliability analysis, proposing a novel method termed RVM-HIS. The RVM-HIS demonstrates exceptional computational efficiency, making it eminently suitable for rare events reliability analysis with implicit performance function. Moreover, the computational efficiency of RVM-HIS has been significantly enhanced through the improvement of the U learning function.