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This study aims to comprehensively examine the relationship between initial public offering (IPO) activities and macroeconomic factors in Sri Lanka.

This study uses principal component analysis (PCA) and autoregressive distributed lag (ARDL) techniques to examine the relationship between IPO activities and macroeconomic factors. Ten macroeconomic variables are transformed into principal components (factors) using PCA. Then, ARDL is applied to investigate the long- and short-term relationships between IPO activities and the transformed macroeconomic factors.

The empirical investigation identifies three principal factors from the ten macroeconomic variables, of which two factors have a significant long-run association with IPO activities: “return on investment (RTOI)” and “economic and market development (ECMD).” In the short run, “trade openness and banking sector development (TOBD)” and RTOI are significantly associated with IPO activities.

The study was based on 30 years of observations, which passed all diagnostic tests but may be insufficient for generalizing the findings. Future studies could use high-frequency data (monthly or quarterly) to increase the number of observations and repeat the method and analysis. Also, while the symmetrical ARDL method was used in this study, an asymmetrical ARDL method may provide more insightful results and interpretations.

The study highlights the importance of considering both long- and short-term associations when analyzing the impact of macroeconomic variables on IPO activities.

This study is the first to comprehensively examine the relationship between IPO activities and macroeconomic variables using PCA and the ARDL technique. The study provides insight into the macroeconomic factors that influence IPO activities in Sri Lanka and highlights the importance of considering long- and short-term associations.

Business competitiveness is critical for a thriving economy that requires companies to be more efficient and innovative to outperform their rivals. This paper investigates the main determinants of business competitiveness from the resource-based view (RBV) perspective.

Data were collected from 140 discrete and large manufacturing firms in Malaysia through a cross-sectional quantitative-based survey with a convenience sampling procedure. The findings from the PLS-SEM analysis showed that implementing LAG manufacturing significantly amplifies business competitiveness.

It was found that cost leadership strategy drives lean and agile manufacturing implementation, while differentiation positively amplifies the implementation of lean, agile and green manufacturing. This study contributes to the body of knowledge and provides insight to practitioners in tailoring strategies to steer manufacturing firms toward being more competitive.

This study identifies the effect of LAGP implementation on business competitiveness. This paper will benefit practitioners and managers by providing insights into tailoring strategies to steer manufacturing firms towards being more competitive. This paper follows a structure that includes: an introduction to the study, a review of relevant literature on business competitiveness, lean, agile and green manufacturing implementation, the development of hypotheses, the presentation of research methodology and findings, and finally, a conclusion with a discussion, implications, limitations and suggestions for future research.

To evaluate some of the current discussions about the possible impacts of social networks on the development of gastronomy in the Republic of Serbia. There could be either positive and/or negative impacts and this viewpoint provides some reflection on what the future might hold for some if not many tourism destinations in Serbia and the region when the tourism industry restarts after the pandemic of Covid-19 virus.

The research was conducted in December 2021, on a total of 244 respondents in three cities in Serbia. SPSS software was used, version 26.00, and the obtained data were analyzed by descriptive statistics. Then, to determine the structure of the questionnaire and the percentage of variance, an exploratory factor analysis was performed together with a higher order factor analysis, in order to obtain the desired number of factors. Subsequently, the authors used multiple regression analysis to confirm the significance of the predictors. The goal of the research was to determine whether, and to what extent, social networks can predict the choice of restaurants and gastronomic offers in Serbia. Serbian gastronomy has a great influence on the development of tourism, so this research has a wide scientific and practical contribution.

This paper provides a context and viewpoint on the possible implications of impacts of social networks on the development of gastronomy in the Republic of Serbia in the future. It has been proven that social networks can have an impact on the development of gastronomy and tourism itself.

To examine the impact of social networks on the development of gastronomy, the authors conducted a survey online due to the current Covid-19 pandemic. The limitation of this research was precisely that the authors did not have the opportunity to conduct the research live due to the Covid-19 pandemic. It is recommended that such surveys be conducted live in direct contact with respondents in the future in order to obtain a larger sample with fully completed questionnaires.

The importance of social networks is increasingly a topic of study of world research, especially when it comes to gastronomy, which is becoming increasingly important as an activity in the tourism industry. The results indicate that the greatest importance in predicting the choice of restaurants and gastronomic offers has social networks and marketing. The importance of the work is reflected in the recognition of the importance of social networks, in order to better place Serbian gastronomy.

This paper offers a synthesis of views that fosters an understanding of the possibility of impacts of social networks on the development of gastronomy in the Republic of Serbia before and after the Covid-19 pandemic.

The viewpoint proffered in this paper provides scope for a rapid evaluation of the current status of gastronomy tourism in Serbia which can help practitioners and researchers in the faster and better development of gastronomy and tourism.

We adopt an information risk view and argue that higher levels of pledge risk incurred by insiders incentivize opportunistic financial disclosure and impair the quality of information available to analysts to forecast firm performance.

We sample Chinese listed companies from 2010 to 2022. Following the literature, we apply established models to measure and test analysts’ forecasting accuracy/dispersion related to controlling shareholders pledging equity and the amount of margin call pressure. Analyst characteristics and nonfinancial disclosures proxied by CSR reports are also examined as factors likely to influence the relationship between pledge risk and analysts’ forecast quality.

We find that analysts’ earnings predictions are less accurate and more dispersed as the proportion of shares pledged (pledge ratio) increases and in combination with greater margin call pressure. Pledge ratios are significantly associated with several information risk proxies (i.e. earnings permanence, accruals quality, audit quality, financial restatements, related party transactions and internal control weaknesses), validating the channel through which equity pledges undermine analysts’ forecast quality. The results also demonstrate that forecast quality declines for a wide variety of analysts’ attributes, including high- and low-quality analysts and analysts from small and large brokerage firms. Importantly, nonfinancial disclosures, as proxied by CSR reporting, improve analysts’ forecasts.

We extend the literature by demonstrating that incremental pledge risk increases non-diversifiable information risk; all non-pledging shareholders pay a premium through more diverse and less accurate earnings forecasts. Our study provides important policy implications with economically significant costs to investors associated with insider equity pledges. Our results highlight the benefits of nonfinancial disclosures in China, which has implications for the current debate on the global convergence of CSR reporting.

This study analyzes whether industry relatedness between a corporate borrower and its group peers significantly affects that firm's borrowing cost.

A regression analysis is run on bank-loan data of a sample of Indonesian companies for 2010–2020. The main variables of interest are the natural logarithms of the borrowing firm's number of affiliates classified within either similar 2- or 4-digit GICS industries, and the Caves weighted index of these firms' related diversification. This index measures how firms in a group are diversified in relation to the borrower. The dependent variable is the all-in credit spread, stated in basis points, over the LIBOR or similar benchmark, as of the loan issuance date.

Findings support the industry-relatedness hypothesis and contradict the risk-reduction hypothesis and show that banks charge lower loan spreads on a borrowing firm that either operates within a similar industry as its affiliate or diversifies into related sectors or industries. Consistent with the co-insurance-effect hypothesis, the results also underline the importance of the parent and first-layer firms as supporting instead of the tunneling vehicles within business groups. These conclusions hold even after segregating the sample and using the loan maturity as the dependent variable.

This study uses a unique diversification measurement based on the borrowing firm's sector or industry, relative to other group members, and offers new insights on business group diversification and bank loan costs.

High-efficiency video coding (HEVC) is the latest video coding standard that has better coding efficiency than the H.264/advanced video coding (AVC) standard. The purpose of this paper is to design and develop an effective block search mechanism for the video compression-HEVC standard such that the developed compression standard is applied for the communication applications.

In the proposed method, an rate-distortion (RD) trade-off, named regressive RD trade-off is used based on the conditional autoregressive value at risk (CaViar) model. The motion estimation (ME) is based on the new block search mechanism, which is developed with the modification in the Ordered Tree-based Hex-Octagon (OrTHO)-search algorithm along with the chronological Salp swarm algorithm (SSA) based on deep recurrent neural network (deepRNN) for optimally deciding the shape of search, search length of the tree and dimension. The chronological SSA is developed by integrating the chronological concept in SSA, which is used for training the deep RNN for ME.

The competing methods used for the comparative analysis of the proposed OrTHO-search based RD + chronological-salp swarm algorithm (RD + C-SSA) based deep RNN are support vector machine (SVM), fast encoding framework, wavefront-based high parallel (WHP) and OrTHO-search based RD method. The proposed video compression method obtained a maximum peak signal-to-noise ratio (PSNR) of 42.9180 dB and a maximum structural similarity index measure (SSIM) of 0.9827.

In this research, an effective block search mechanism was developed with the modification in the OrTHO-search algorithm along with the chronological SSA based on deepRNN for the video compression-HEVC standard.

The purpose of our study is to examine the functioning of internal capital markets (ICMs) within business groups in Iran. We document how the ultimate owner's economic interests in affiliated firms influence their investment and dividend policies.

Using hand-collected data on the ownership structures of Iranian firms, we first identify group-affiliated firms using Almeida et al.’s (2011) method. Having identified business groups, we test a number of hypotheses concerning the dynamics of the ICMs and the implications of the ultimate owner’s incentives for affiliated firms’ behavior.

We first demonstrate that investments of group-affiliated firms are less sensitive to their own cash flow (as compared to stand-alone firms) but are sensitive to the cash flows of other firms affiliated with the same group near or at the bottom of the ownership structure. We next find significant variation in dividend policy within groups, with notably higher dividends for firms close to the ultimate owner. Furthermore, we find that higher investments by firms close to the owner lead to lower dividends by firms positioned far from the owner, but the reverse does not hold.

We are the first to examine the effect of group-affiliated firms’ investments on the dividend policies of other firms based on their position within the group. Our findings illuminate how business groups prioritize funding investments in their closely held firms over paying dividends to outside investors in firms positioned farther from the group owner.

This paper examines the relationship between a pyramidal firm’s control-ownership wedge and the amount of its debt relative to the group’s total debt and its likelihood of having guaranteed debt in its capital structure.

The study sample consists of the 200 largest Indonesian companies listed on the Indonesia Stock Exchange for the period 2015–2022. I run baseline regressions and a number of robustness tests, which include two-stage least squares, censored regressions, difference-in-differences and subsample regressions as well as regressions with interaction terms.

The results show that, within pyramidal business groups, member firms with large control-ownership wedges are associated with less group debt allocation and a higher probability of having guaranteed debt.

To the best of my knowledge, this paper is the first to examine the direct link between a pyramidal firm’s control wedge and its’ proportion of group debt allocation and probability of having guaranteed debt. Therefore, it enriches the theory of tradeoffs within business groups and sheds more insights on the intragroup guarantees literature.

This study aims to investigate the use of social networking sites (SNS) by researchers and their behaviours when conducting research-related activities by applying the unified theory of acceptance and use of technology (UTAUT) theory.

An online survey was distributed. This study’s design is derived from the UTAUT framework’s questionnaire items. The sample of this study comprised 216 respondents from 40 universities in the United Kingdom. Descriptive statistics were used to analyse the data.

Respondents revealed a positive relationship between the four constructs of the UTAUT framework (performance expectancy, effort expectancy, social influence and facilitating condition) associated with their intention to use SNS.

Most of the respondents were from the University of Strathclyde, so the authors cannot generalize the findings to other universities.

The findings will offer an extensive understanding of the value of SNSs, which will aid researchers to increase their visibility, and research activities online.

The results will provide an in-depth knowledge of the importance of SNSs, helping scholars to become more visible and engage in online research. A number of factors impacted how researchers behaved on SNSs and what they intended to use for research-related activity. School administrators, experts and other sponsors could take action to promote the use of SNSs in educational settings based on the findings. The study’s findings offer insightful knowledge to those who create SNS websites. By using this information, they will be able to improve these sites for research and study and gain a better understanding of the demands of SNS users.

This study aims to examine how mental health symptoms and social support predict changes in online and in-person social networks among gamers over time. Although research has explored how social networks influence mental health, less is known about how mental health shapes the evolution of social connections in gaming contexts where relationships can form and dissolve fluidly.

Adult gamers (n = 236) completed surveys at two time points approximately six months apart measuring mental health symptoms (depressive symptoms, anxiety), perceived social support and characteristics of both their in-person and gaming-based social networks. Partial least squares regression models examined how Time 1 mental health and support measures predicted changes in network characteristics while controlling for baseline network measures.

Results revealed distinct patterns of network evolution across contexts. Higher initial depressive symptoms predicted strengthening of in-person relationships but decreases in online relationship quality over time. Anxiety emerged as a particularly influential predictor of online network development, with higher baseline anxiety associated with decreased closeness, confiding behavior and positive interactions in gaming relationships. Strong initial gaming community integration predicted decreased quality of in-person relationships, suggesting potential competition between virtual and physical social spheres.

This study provides longitudinal examination of how mental health symptoms distinctly influence the evolution of social networks across online and offline contexts among gamers. The findings demonstrate that different symptoms show unique patterns of association with network development over time, challenging assumptions about gaming spaces serving as universally accessible social environments.