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Dynamic advertising, including television and online video ads, demands new theory and tools developed to understand attention to moving stimuli. The purpose of this study is to empirically test the predictions of a new dynamic attention theory, Dynamic Human-Centred Communication Systems Theory, versus the predictions of salience theory.

An eye-tracking study used a sample of consumers to measure visual attention to potential areas of interest (AOIs) in a random selection of unfamiliar video ads. An eye-tracking software feature called intelligent bounding boxes (IBBs) was used to track attention to moving AOIs. AOIs were coded for the presence of static salience variables (size, brightness, colour and clutter) and dynamic attention theory dimensions (imminence, motivational relevance, task relevance and stability).

Static salience variables contributed 90% of explained variance in fixation and 57% in fixation duration. However, the data further supported the three-way interaction uniquely predicted by dynamic attention theory: between imminence (central vs peripheral), relevance (motivational or task relevant vs not) and stability (fleeting vs stable). The findings of this study indicate that viewers treat dynamic stimuli like real life, paying less attention to central, relevant and stable AOIs, which are available across time and space in the environment and so do not need to be memorised.

Despite the limitations of small samples of consumers and video ads, the results of this study demonstrate the potential of two relatively recent innovations, which have received limited emphasis in the marketing literature: dynamic attention theory and IBBs.

This study documents what does and does not attract attention to video advertising. What gets attention according to salience theory (e.g. central location) may not always get attention in dynamic advertising because of the effects of relevance and stability. To better understand how to execute video advertising to direct and retain attention to important AOIs, advertisers and advertising researchers are encouraged to use IBBs.

This study makes two original contributions: to marketing theory, by showing how dynamic attention theory can predict attention to video advertising better than salience theory, and to marketing research, showing the utility of tracking visual attention to moving objects in video advertising with IBBs, which appear underutilised in advertising research.

This study aims to investigate the differences in the extent of non-financial disclosure (NFD) across companies listed on the Warsaw Stock Exchange over the period surrounding the implementation of the Directive 2014/95/EU.

The sample comprising 134 selected companies. Content analysis and a disclosure index were used to measure the level of NFD. Non-financial reporting practices in the two years before (2015) and one year after (2017) the implementation of the Directive were compared.

The results highlight that there is already a high level of compliance with the European Union’s regulation. The extent of the NFD across different thematic aspects in reporting media increased significantly between 2015 and 2017 in particular in human rights and anti-corruption. The Directive had the largest impact on those firms with previously low levels of NFD and led to more homogeneity of NFD across different industries.

The study contributes to the understanding of the impact of the Directive on the NFD practices by European Union companies. The research has important implications for policymakers because it revealed that mandatory regulations form a crucial instrument in improving the harmonization of NFD. The research suggests that, due to the Directive, stakeholders should be provided with more comprehensive information that they need in their decision-making process.

This paper aims to analyze the direct and indirect effects of investor protection on forced CEO turnover.

The authors investigate 5,175 firm-year observations from 16 European countries over 2012–2018, collect data on four national investor protection indicators, identify 196 forced CEO turnovers and use multiple logistic regression models.

The results show that a reduction in the degree of investor protection significantly increases the probability of a forced change of the company’s CEO. Furthermore, when the degree of investor protection increases, directors are attributed a lower degree of responsibility in the event of a decline in earnings performance. Therefore, the relation between a decrease in profitability and a forced change of CEO is reduced.

The research is focused on countries belonging to the European Economic Area and most of the investor protection indicators are derived from surveys. Concerning policy implications, the findings suggest that regulators should focus on the effective enforcement of investor protection mechanisms.

The results confirm that characteristics at the country level have an impact on corporate decisions, highlighting the importance of increasing the degree of investor protection as a means of mitigating agency conflicts and improving stewardship.

To the best of the authors’ knowledge, this study explores a relatively underinvestigated topic as it uses investor protection indicators to jointly evaluate both direct and indirect effects on forced changes of CEO through cross-national research.

The purpose of this paper is to examine the effectiveness of an improved dummy variables control grey model (DVCGM) considering the hysteresis effect of government policies in China's energy intensity (EI) forecasting.

Energy consumption is considered as an important driver of economic development. China has introduced policies those aim at the optimization of energy structure and EI. In this study, EI is forecasted by an improved DVCGM, considering the hysteresis effect of energy-saving policies of the government. A nonlinear optimization method based on particle swarm optimization (PSO) algorithm is constructed to calculate the hysteresis parameter. A one-step rolling mechanism is applied to provide input data of the prediction model. Grey model (GM) (1, N), DVCGM (1, N) and ARIMA model are applied to test the accuracy of the improved DVCGM (1, N) model prediction.

The results show that the improved DVCGM provides reliable results and works well in simulation and predictions using multivariable data in small sample size and time-lag virtual variable. Accordingly, the improved DVCGM notes the hysteresis effect of government policies and significantly improves the prediction accuracy of China's EI than the other three models.

This study estimates the EI considering the hysteresis effect of energy-saving policies in China by using an improved DVCGM. The main contribution of this paper is to propose a model to estimate EI, considering the hysteresis effect of energy-saving policies and improve forecasting accuracy.

Structural equation modeling (SEM) has been widely used to examine complex research models in international business and marketing research. While the covariance-based SEM (CB-SEM) approach is dominant, the authors argue that the field’s dynamic nature and the sometimes early stage of theory development more often require a partial least squares SEM (PLS-SEM) approach. The purpose of this paper is to critically review the application of SEM techniques in the field.

The authors searched six journals with an international business (and marketing) focus (Management International Review, Journal of International Business Studies, Journal of International Management, International Marketing Review, Journal of World Business, International Business Review) from 1990 to 2013. The authors reviewed all articles that apply SEM, analyzed their research objectives and methodology choices, and assessed whether the PLS-SEM papers followed the best practices outlined in the past.

Of the articles, 379 utilized CB-SEM and 45 PLS-SEM. The reasons for using PLS-SEM referred largely to sampling and data measurement issues and did not sufficiently build on the procedure’s benefits that stem from its design for predictive and exploratory purposes. Thus, the procedure’s key benefits, which might be fruitful for the theorizing process, are not being fully exploited. Furthermore, authors need to better follow best practices to truly advance theory building.

The authors examined a subset of journals in the field and did not include general management journals that publish international business and marketing-related studies. Fur-thermore, the authors found only limited use of PLS-SEM in the journals the authors considered relevant to the study.

The study contributes to the literature by providing researchers seeking to adopt SEM as an analytical method with practical guidelines for making better choices concerning an appropriate SEM approach. Furthermore, based on a systematic review of current practices in the international business and marketing literature, the authors identify critical challenges in the selection and use of SEM procedures and offer concrete recommendations for better practice.

This paper focuses on Ṣukūk issuance determinants in Gulf Cooperation Council (GCC) countries. Given the dual characteristic of debt and equity of Ṣukūk as well as their unique benefits of social responsibility, the author questions whether the theories of capital structure, the trade-off and the pecking order are able to well explain the Ṣukūk issuance.

First, the author verifies these theories using capital structure determinants and regresses the Ṣukūk change on these determinants. Second, the author tests the trade-off theory with the target debt model and third, verifies the pecking order theory using the fund flow deficit model.

The empirical results show that capital structure determinants fail to explain both theories. The author confirms that the Ṣukūk change is significatively linked to the deviation from a Ṣukūk target. So, issuing firms balance the marginal costs of Ṣukūk and their benefits of religiosity and social responsibility toward a target debt. The author finds no evidence of the pecking order theory.

This study contributes to corporate finance theory and corporate social responsibility. It verifies if capital structure theories proved in conventional financing can well explain Islamic bonds issuance given their social responsibility benefits.

Managers and investors would pay attention to the social factors explaining Ṣukūk issuance in their finance and investment decisions. They would be enhanced to use this financing tool knowing its social unique benefits. This also should encourage governments to enhance this socially responsible financing. Rating agencies would be motivated to evaluate Ṣukūk and firms would improve the quality and relevance of disclosure to get the best rating.

The author highlights the social factors explaining Ṣukūk issuance and enhances corporate social responsibility (CSR).

The author extends the few literature testing capital structure theories for Islamic bonds and highlights the specific social responsible features of Ṣukūk that would bridge their issuance to capital structure theories. So the author enhances the concept of Islamic CSR. Tying capital structure theories to CSR would also help developing Islamic finance theory as a unique social responsible framework.

This paper aims to introduce a crowd-based method for theorizing. The purpose is not to achieve a scientific theory. On the contrary, the purpose is to achieve a model that may challenge current scientific theories or lead research in new phenomena.

This paper describes a case study of theorizing by using a crowd-based method. The first section of the paper introduces what do the authors know about crowdsourcing, crowd science and the aggregation of non-expert views. The second section details the case study. The third section analyses the aggregation. Finally, the fourth section elaborates the conclusions, limitations and future research.

This document answers to what extent the crowd-based method produces similar results to theories tested and published by experts.

From a theoretical perspective, this study provides evidence to support the research agenda associated with crowd science. The main limitation of this study is that the crowded research models and the expert research models are compared in terms of the graph. Nevertheless, some academics may argue that theory building is about an academic heritage.

This paper exemplifies how to obtain an expert-level research model by aggregating the views of non-experts.

This study is particularly important for institutions with limited access to costly databases, labs and researchers.

Previous research suggested that a collective of individuals may help to conduct all the stages of a research endeavour. Nevertheless, a formal method for theorizing based on the aggregation of non-expert views does not exist. This paper provides the method and evidence of its practical implications.

This paper aims to strive to close the current research gap pertaining to potential implications of the blockchain for supply chain management (SCM) by presenting a framework built on four established economic theories, namely, principal agent theory (PAT), transaction cost analysis (TCA), resource-based view (RBV) and network theory (NT). These theories can be used to derive research questions that are theory-based as well as relevant for the industry. This paper is intended to initiate and stimulate an academic discussion on the potential impact of the blockchain and introduces a framework for middle-range theorizing together with several research questions.

This paper builds on previous theories that are frequently used in SCM research and shows how they can be adapted to blockchain-related questions.

This paper introduces a framework for middle-range theorizing together with several research questions.

The paper presents blockchain-related research questions derived from four frequently used theories, namely, PAT, TCA, RBV and (NT). These questions will guide future research pertaining to structural (PAT, TCA) and managerial issues (RBV, NT) and will foster middle-range theory development in SCM research.

Blockchain technology has the potential to significantly change SCM. Given the huge investments by industry, academic research is needed which investigates potential implications and supports companies. In this paper, various research questions are introduced that illustrate how the implications of blockchain on SCM can be investigated from different perspectives.

To the best of the author’s knowledge, no academic papers are published in leading academic journals that investigate the relationship between SCM and blockchain from a theory-based perspective.