Search results

A gap between research and practice is commonly perceived throughout accounting academia. However, empirical evidence on the magnitude of this detachment remains scarce. The authors provide new evidence to the ongoing debate by introducing a novel topic-based approach to capture the research-practice gap and quantify its extent. They also explore regional differences in the research-practice gap.

The authors apply the unsupervised machine learning approach Latent Dirichlet allocation (LDA) to compare the topical composition of 2,251 articles from six premier research, practice and bridging journals from the USA and Europe between 2009 and 2019. The authors extend the existing methods of summarizing literature and develop metrics that allow researchers to evaluate the research-practice gap. The authors conduct a plethora of additional analyses to corroborate the findings.

The results substantiate a pronounced topic-related research-practice gap in accounting literature and document its statistical significance. Moreover, the authors uncover that this gap is more pronounced in the USA than in Europe, highlighting the importance of institutional differences between academic communities.

The authors objectify the debate about the extent of a research-practice gap and stimulate further discussions about explanations and consequences.

To the best of the authors' knowledge, this is the first paper to deploy a rigorous machine learning approach to measure a topic-based research-practice gap in the accounting literature. Additionally, the authors provide theoretical rationales for the extent and regional differences in the research-practice gap.

This study aims to empirically test how sponsored video customization (i.e. the degree to which a sponsored video is customized for a sponsoring brand) affects video shares differently depending on influencer characteristics (i.e. mega influencer and expert influencer) and brand characteristics (i.e. brand establishment and product involvement).

This study uses a unique real-world data set that combines coded variables (e.g. customization) and objective video performance (e.g. sharing) of 365 sponsored videos to test the hypotheses. A negative binomial model is used to analyze the data set.

This study finds that the effect of video customization on video shares varies across contexts. Video customization positively affects shares if they are made for well-established brands and high-involvement products but negatively influences shares if they are produced by mega and expert influencers.

This study extends the influencer marketing literature by focusing on a new media modality – sponsored video. Drawing on the multiple inference model and the persuasion knowledge theory, this study teases out different conditions under which video customization is more or less likely to foster audience engagement, which both influencers and brands care about. The chosen research setting may limit the generalizability of the findings of this study.

The findings suggest that mega and expert influencers need to consider if their endorsement would backfire on a highly customized video. Brands that aim to engage customers with highly-customized videos should gauge their decision by taking into consideration their years of establishment and product involvement. For video-sharing platforms, especially those that are planning to expand their businesses to include “matching-making services” for brands and influencers, the findings provide theory-based guidance on optimizing such matches.

This paper fulfills an urgent research need to study how brands and influencers should produce sponsored videos to achieve optimal outcomes.

This paper aims to meta-analyze the results of the prior studies related to the relationship of human capital and financial performance in Islamic banking.

To examine the relationship between human capital and financial of Islamic banks, 23 empirical studies having sample of 15,607 are considered for the meta-analysis. Moreover, different measures related to financial performance including return on assets (ROA), return of equity (ROE) and Tobin’s Q have been taken as moderating for further subgroup analysis.

The results of meta-analysis reveal a positive correlation between human capital and financial performance with an effect size of 0.268. The subgroup analyses showed significant positive associations of human capital with ROA and ROE, insignificant with Tobin’s Q.

This study suggests Islamic banking should prioritize human capital development, maintain consistency and adopt a long-term perspective. Future research should consider context-specific factors and harmonize human capital and financial performance measurements for consensus.

This study aims to investigate the impact of the transformational leadership style on the behaviour of restaurant employees. Also, it was aimed to investigate the effect of transformational leadership on trust and the effect of trust on altruistic intention and organizational commitment.

The study integrates insights from transformational leadership to provide a fresh perspective to advance comparative organizational behaviour research. To test the hypotheses, the authors conduct a multiple analysis with observations from Turkey getting staff in culinary department with a quantitative survey.

This study equips different professional entities in the food and beverage industry with useful, contextualized links between transformational leadership. According to results, the perspective of transformational leadership style affects the concepts of trust, altruistic value and organizational commitment positively. Charisma, moral modelling and individualized consideration had a significant effect on trust. Also, trust has a significant effect on altruistic intention and organizational commitment.

The present study incorporated confidence as a mediating variable; however, it is recommended that alternative scales be used in subsequent research endeavours. Future research endeavours may incorporate theoretical frameworks such as theory of planned behaviour or stimulus-organism-response.

Transformational leadership style is a good acquisition for restaurant employees. There is a healthier and safer job sharing in these restaurants. This can be interpreted as a more satisfied customer. A good leader has a great contribution to the future and sustainability of the business.

This research created a new model and examined employees’ views on the company and its management. As a result of the analysis, it was determined that charisma, moral modelling and individualized consideration had a significant effect on trust.

This assists in learning better service quality developing and business practices to augment culinary staff, thereby maximizing their valuable contributions to tourism growth. This research created a new model and examined employees’ views on the company and its management.

This study aims to assess the impact of personality traits, risk perception and perceived coronavirus disease 2019 (COVID-19) disruption on the investment behavior of individual investors in the Indian stock market.

This study adopts a survey approach. The sample comprises 315 active retail investors investing in the Indian stock exchange. Two-stage analysis technique regression and Artificial Neural Network (ANN) were used for data analysis. Study hypotheses were tested through regression and ANN was adopted to validate the regression results.

Two regression models were modeled to test the research hypotheses. Findings showed that risk perception and COVID-19 disruption have a significant positive and neuroticism has a significant negative impact on short-term investment decisions, while the role of conscientiousness in determining short-term investment decisions was not found significant. Results also showed a positive impact of neuroticism and conscientiousness and a negative impact of risk perception on long-term investment decisions. The role of COVID-19 disruption was found negative but insignificant in predicting long-term investment decisions.

This study has practical implications for many parties like retail investors, financial advisors and policymakers. This study will assist the investors to realize that they do not always take rational financial decisions. This study will suggest the financial advisors to use the knowledge of behavioral finance in making the advisors' advisory and wealth management decisions. This study will also assist the policymakers to outline behaviorally well-informed policy decisions to protect the interests of investors.

India is one of the fast-growing economies in the world. India has a vast population of active investors and determining investors' investment behavior adds novelty to this study as developed economies have remained the main focus of previous studies. The other novel feature of this study is that this study tries to assess the impact of COVID-19 disruption along with personality traits and risk perception on investment behavior. The other valuable factor of this study is the use of ANN to predict the relative importance of the exogenous variables.

As a result, the current study attempted to investigate the impact of green human resource (GHR) practices on long-term performance, and the path has been explained through organizational identification, which is supported by social identity theory.

To achieve the present study's primary goal, data were obtained from manufacturing businesses and analyzed using partial least square (Smart PLS) on the data of 284 Pakistani small and medium-sized enterprises (SMEs) registered with the small and medium-sized enterprises development authority (SMEDA).

As a result, the findings show that organizational identification explains the indirect relationship between sustainable performance and green human resource management (GHRM).

To limit the limited negative effect on the environment and society, the findings provide several suggestions for the government authorities and policymakers to adopt green practices and policies.

Green practices are essential for a company to limit its negative environmental effect. Environmental critical problems among shareholders put pressure on the firm to implement GHR practices and organizational identification with long-term success.

The purpose of the cross-cultural study is three-fold – (1) to examine the effect of agile strategic human resource management (ASHRM) practices for each stage of the employee life-cycle on employee outcomes, (2) to investigate employee outcomes – organisational outcome linkage and (3) to explore the link between organisational outcomes and shared values to society.

The research used random sampling to select 674 managers (358 from India and 316 from Thailand) who work in food processing firms. A structured questionnaire was administered to the respondents separately for collecting data. The authors used PLS-SEM to verify the study hypotheses and related research models.

The multi-group analysis (MGA) results indicated a significant difference in agile SHRM practices, employee outcomes, organisational outcomes and shared values in the Indian and Thai samples. However, the difference in the impact of the organisational outcome on shared values to society was found to be insignificant, suggesting that organisational outcome had a similar impact on shared values in both countries.

The agile strategic HR practices, especially talent acquisition, learning and development, reward and recognition, must be aligned to suit country-specific culture for improving job satisfaction, employee engagement and employee productivity, which would result in improved organisational outcomes such as profitability and customer satisfaction, ultimately enhancing shared values to society. This comparative analysis would also help the Indian and Thai food sectors develop new strategies or alter existing ones in light of the ASHRM model.

The study provides an innovative ASHRM framework from a cross-cultural perspective, which may help organisations to adopt agile talent acquisition, career development and separation strategies to thrive in the turbulent international business environment.

This study examines the impact of raising the ceiling value of Electronic Commerce Custom Declarations (ECCD) on Turkey's export performance processed via ECCD during the COVID-19 period.

This paper examines the impact of the pandemic conditions on Cross-Border Electronic Commerce (ECCD) exports from Turkey to 47 countries over 42 months before and during the pandemic. An empirical analysis using the Pooled Mean Group (PMG) and Mean Group (MG), Panel Autoregressive Distributed Lag (ARDL) approach was conducted to identify the factors affecting export flows.

The findings suggest that raising the ceiling of the ECCD trade is a vital factor in increasing exports. and this result is robust after controlling for pandemic conditions. On the other hand, although the COVID-19 shock mitigates the export volume of ECCD in the short run, it changes by reversal and increases the export level in the long run. Additionally, the number of COVID-19 cases and deaths in Turkey have a significant and negative impact on export flows in the short run, while they have a positive and significant effect in the long run.

The results of this study have practical implications for policymakers, emphasizing the potential and significance of Cross-Border E-Commerce (CBEC) trade.

The study is a pioneering effort in the literature of CBEC to explore how changes in the upper limit on customs declarations can affect export flows, taking into account the impact of the COVID-19 pandemic.

Drawing on the work of Niklas Luhmann, the paper argues that technology can be viewed as a self-referential system which is autonomous from both human beings and other function systems of society. The paper aims to develop a philosophy of technology from the work of Niklas Luhmann. To achieve this aim, it draws upon the systems-theory work of Jacques Ellul, a philosopher of technology who focuses on the autonomous potential of technological evolution.

The paper draws on the work of Niklas Luhmann and Jacques Ellul to explore the theme of autonomous technology and what this means for our thinking about technological issues in the twenty-first century. Insights from these two thinkers and researchers working in the Luhmannian sociological tradition are applied to remote work.

The sociological approach of Luhmann, coupled with Ellul's insights into the autonomous nature of technology, can help us develop a systems theory of technology which takes seriously its irreducibility to human functions.

The paper contributes to the growing sociological literature that thematizes the Luhmannian approach to technology, helping us better understand this phenomenon and think in new ways about what technological autonomy means.

The paper brings together the work of Luhmann, Ellul and contemporary researchers to advance a new understanding of technology and technological communication.

The purpose of this study is to analyse and compile the literature on various option pricing models (OPM) or methodologies. The report highlights the gaps in the existing literature review and builds recommendations for potential scholars interested in the subject area.

In this study, the researchers used a systematic literature review procedure to collect data from Scopus. Bibliometric and structured network analyses were used to examine the bibliometric properties of 864 research documents.

As per the findings of the study, publication in the field has been increasing at a rate of 6% on average. This study also includes a list of the most influential and productive researchers, frequently used keywords and primary publications in this subject area. In particular, Thematic map and Sankey’s diagram for conceptual structure and for intellectual structure co-citation analysis and bibliographic coupling were used.

Based on the conclusion presented in this paper, there are several potential implications for research, practice and society.

This study provides useful insights for future research in the area of OPM in financial derivatives. Researchers can focus on impactful authors, significant work and productive countries and identify potential collaborators. The study also highlights the commonly used OPMs and emerging themes like machine learning and deep neural network models, which can inform practitioners about new developments in the field and guide the development of new models to address existing limitations.

The accurate pricing of financial derivatives has significant implications for society, as it can impact the stability of financial markets and the wider economy. The findings of this study, which identify the most commonly used OPMs and emerging themes, can help improve the accuracy of pricing and risk management in the financial derivatives sector, which can ultimately benefit society as a whole.

It is possibly the initial effort to consolidate the literature on calibration on option price by evaluating and analysing alternative OPM applied by researchers to guide future research in the right direction.