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This study aims to investigate the motivations for the adoption of Industry 4.0 technologies among manufacturing firms in developing economies. Specifically, the effects of relative advantage of the technologies, competitive pressure, and government support on the adoption are explored. Moreover, the mediating role of top management support between environmental factors (government support and competitive pressure) and the adoption of Industry 4.0 technologies is examined.

A research model is developed based on the technology-organization-environment (TOE) framework strengthened by institutional theory. Structural equation modeling (SEM) approach is employed to evaluate the model using data obtained from 215 manufacturing firms through a cross-industry survey. Additionally, a post-hoc analysis is conducted using cluster analysis and ANOVA.

The results show that competitive pressure and government support significantly promote top management support, which in turn contributes to the adoption of Industry 4.0 technologies. Relative advantage of the technologies is not significantly related to the adoption.

This study does not explore the relationship between technology type and the specific needs of manufacturing firms. Future researchers can conduct a more comprehensive analysis by examining how different technology types align with the unique needs of individual companies.

The findings of this study have implications for both policymakers and managers. Policymakers can leverage these insights to understand the underlying motivations behind manufacturing firms' adoption of Industry 4.0 technologies and develop promoting policies. In turn, managers should keep an eye on government policies and utilize government support to facilitate technology adoption.

This study uncovers the underlying motivations—government support and competitive pressure—for the adoption of Industry 4.0 technologies among manufacturing firms in developing economies. Meanwhile, it complements previous research by showing the mediating role of top management support between environmental factors (government support and competitive pressure) and the adoption of Industry 4.0 technologies.

This paper aims to examine the association between green innovation and the cost of equity in China. This study relies on the investors’ base perspective and shareholders’ perceived risk perspective to investigate the relation between green innovation and the cost of equity in China.

The paper uses firm-fixed effect regression for a sample of Chinese public companies for the period 2008–2018.

The authors find a negative relationship between green innovation and the cost of equity capital. This negative association is found to be more pronounced for less financially constrained firms, during periods of high economic policy uncertainty, and for firms with a strong internal control environment. Finally, the paper shows that the negative association became more pronounced after the passage of the Environmental Protection Law of China in 2012. The results remain robust to possible endogeneity concerns.

This study contributes to the green innovation literature by documenting that shareholders favorably view firms implementing green innovation policies. The study also has policy implications for Chinese regulators in improving the green credit policy.

Highly committed, motivated and engaged employees assure organizational success and competitiveness. The study aims to examine the association between human resource development (HRD) practices and employee engagement with organizational commitment as a mediating variable.

Data were collected from 760 employees of 13 star-rated hotels comprising 5 (five-star) and 8 (four-star). The data supported the hypothesized relationships. Structural equation modeling was used to evaluate the proposed model and hypotheses. Construct validity and reliability were established through confirmatory factor analysis.

The results indicate that HRD practices and affective commitment are significantly associated. HRD practices and continuance commitment were shown to be non-significantly associated. HRD practices and normative commitment were shown to be non-significantly associated. Employee engagement and organizational commitment are significantly associated. The results further show that organizational commitment mediates the association between HRD practices and employee engagement.

The generalizability of the findings will be constrained due to the research's hotel industry focus and cross sectional data.

The study's findings will serve as valuable pointers for stakeholders and policymakers of the hotel industry in the adoption, design and implementation of proactive HRD interventions to keep highly engaged and committed employees for organizational competitiveness and sustainability.

By evidencing empirically that organizational commitment mediates the nexus between HRD practices and employee engagement, the study extends the literature.

Digital transformation (DT) projects are complex and often unsuccessful. While researchers have suggested many guidelines and best practices on how to successfully roll out DT projects and how they are spread among a large number of scientific papers. The aim of this paper is to synthesize these guidelines into clear overviews.

A systematic literature review was conducted on both Scopus and Web of Science to search for papers suggesting DT guidelines or best practices. In total, 150 papers dealing with DT and guidelines were fully analyzed.

Eight main DT guidelines were found and each one was expanded with several best practices on how to implement these. The results are eight tables giving an overview of the commonly agreed-upon best practices for each DT guideline.

These overviews are useful for both researchers and practitioners, to guide future work and to be inspired respectively. This paper calls for more research on how these guidelines are followed in practice, how these differ per industry and what their impact is on the overall success of DT projects.

The synthesis of DT guidelines organized into an accessible format has not yet been conducted before, and can serve as a seminal pinpoint for future research.

The primary purpose of this paper is to identify the so-called core authors and their publications according to pre-defined criteria and thereby direct the users to the fastest and easiest way to get a picture of the otherwise pervasive field of bankruptcy prediction models. The authors aim to present state-of-the-art bankruptcy prediction models assembled by the field's core authors and critically examine the approaches and methods adopted.

The authors conducted a literature search in November 2022 through scientific databases Scopus, ScienceDirect and the Web of Science, focussing on a publication period from 2010 to 2022. The database search query was formulated as “Bankruptcy Prediction” and “Model or Tool”. However, the authors intentionally did not specify any model or tool to make the search non-discriminatory. The authors reviewed over 7,300 articles.

This paper has addressed the research questions: (1) What are the most important publications of the core authors in terms of the target country, size of the sample, sector of the economy and specialization in SME? (2) What are the most used methods for deriving or adjusting models appearing in the articles of the core authors? (3) To what extent do the core authors include accounting-based variables, non-financial or macroeconomic indicators, in their prediction models? Despite the advantages of new-age methods, based on the information in the articles analyzed, it can be deduced that conventional methods will continue to be beneficial, mainly due to the higher degree of ease of use and the transferability of the derived model.

The authors identify several gaps in the literature which this research does not address but could be the focus of future research.

The authors provide practitioners and academics with an extract from a wide range of studies, available in scientific databases, on bankruptcy prediction models or tools, resulting in a large number of records being reviewed. This research will interest shareholders, corporations, and financial institutions interested in models of financial distress prediction or bankruptcy prediction to help identify troubled firms in the early stages of distress.

Bankruptcy is a major concern for society in general, especially in today's economic environment. Therefore, being able to predict possible business failure at an early stage will give an organization time to address the issue and maybe avoid bankruptcy.

To the authors' knowledge, this is the first paper to identify the core authors in the bankruptcy prediction model and methods field. The primary value of the study is the current overview and analysis of the theoretical and practical development of knowledge in this field in the form of the construction of new models using classical or new-age methods. Also, the paper adds value by critically examining existing models and their modifications, including a discussion of the benefits of non-accounting variables usage.

This article aims to map the expectations of manufacturing companies towards suppliers in terms of implementing improvement activities. The article poses two research questions: RQ1: What kind of improvement of activities do the surveyed producers expect from their suppliers? RQ2: Do factors such as size, capital or implemented systems influence different assessments of the analyzed requirements toward suppliers?

The Computer Assisted Telephone Interview (CATI) technique was used to collect data. The sample consists of 150 producers (employing over 50 people) who were suppliers for enterprises from the automotive, electromechanical and chemical sectors operating in the Polish business-to-business (B2B) market. We analyzed 11 improvement activities, while their correlation structure was examined by exploratory factor analysis.

We have identified three latent factors – risk reduction, product innovation and increasing efficiency – which summarize the main expectations of manufacturing companies towards suppliers. Expectations for these factors are independent of the implemented management system, although the analysis showed higher expectations for product innovation in organizations with the implementation of Kaizen.

The article fills the research gap in the literature. The research results presented in the literature so far have focused on the expectations of enterprises towards suppliers in terms of meeting the criteria for their initial and periodic assessment. The research gap in the article is the result of empirical research presenting the expectations of manufacturers towards suppliers in terms of improving their processes. Based on the findings of the presented study, development trends and implications for managers responsible for purchasing processes and relationships with suppliers can be determined.

This study aims to provide an overview of studies concerning bias in law, particularly in judges’ decisions. The authors intend to bring to light the factors that can most frequently lead to unequal decisions to enable judges to better perform their function.

A literature review was used as a methodology based on studies involving judges and juries.

The evidence reported by this review suggests how difficult the judge’s job is and how they can be unconsciously influenced by inferences, deductions and biases. The results show that the pleasantness of the witness and the confidence they exhibit during testification are crucial factors in influencing the decisions of judges and jurors. From these studies, it can be assumed that different personal aspects – smiling, pleasantness and the witness’s credibility – can be positively associated with each other, which could compromise the ongoing evaluation. Gender is another factor that can influence evaluations; in fact, witnesses are evaluated based on their own “gender” as well as that of the jurors. Another essential factor is self-confidence. Also, the age of both of the judge and of the witness can be a factor that influences decisions in court. Other factors such as communication effectiveness, degree of accuracy of reported information and non-verbal behaviour were also found to be important.

Among the limitations of this research, the authors have to consider the low number of available research and that the most of these derive from a specific cultural context – the American one. There may also be limits to the way in which certain concepts are used in different parts of the world, particularly through a very broad construct, such as the credibility of witness.

This study highlights which inferences and biases can characterise decision-making processes and, above all, highlights the need for specific training courses aimed at managing the many processes involved in influencing human decisions.

The authors believe that this work can raise awareness about the series of unconscious reasoning that may happen in the legal field, which has a major impact on people’s lives and on the general perception of justice.

In this research, the authors have considered some of the criteria that may intervene in the evaluation of witnesses, those present in the current scientific literature. From the research, it seems appropriate and necessary to provide judges with adequate training aimed at the recognition of their cognitive processes and bias. In fact, when they were made aware of them, they were less affected by bias, resulting in more objective and limiting improper inferences.

The increased interest among academicians to explore more about tax management behavior is evident in the literature on corporate tax avoidance. This paper aims to illustrate the multiple aspects that influence the tax avoidance behavior of corporations and its impacts through the systematic review method.

This study used “Tax Avoidance” OR “Tax Aggressiveness” OR “Tax Planning” as search strings to extract the relevant literature from the Scopus database. This study is a comprehensive analysis of existing literature on corporate tax avoidance behavior. Further, the keyword network analysis has been used to find out the most explored and dry research areas related to corporate tax avoidance behavior using VOSviewer software.

The study finds that taxation decision is an important managerial decision. Managers adopt tax avoidance tactics to boost postax profits to meet the shareholders’ expectations, particularly of risk-averse shareholders, and sometimes for their benefit also. With this, this study also finds that firms’ characteristics, political connections and corporate social responsibility activities also impact taxation decisions. In addition, the study identifies that tax-avoiding behavior has a contradictory impact on firm value, market growth and corporate transparency disclosure decisions.

The study assists the researchers by providing a brief overview of tax avoidance behavior, for corporates in understanding the implications of tax avoidance, and for policymakers to fix the taxation loopholes and bring necessary tax reforms.

This study adds to the existing literature by providing a thorough overview of theories, determinants and outcomes of corporate tax avoidance behavior.

Globalization occupies a central research activity and remains an increasingly controversial phenomenon in economics. This phenomenon corresponds to a subject that can be criticized through its impact on national economies. On the other hand, the world economy is evolving in a liberalized environment in which foreign direct investment plays a fundamental role in the economic development of each country. The advent of financial flows – foreign direct investment, remittances and official development assistance – can be a key factor in the development of the economy. The purpose of this study is to analyze the effect of financial flows on economic growth in developing countries. Empirically, different approaches have been used. As part of this study, an attempt was made to use a combined autoregressive distributed lag (ARDL) panel approach to study the short-term and long-run effects of financial flows on economic growth. The results indicate ambiguous effects. Economically, the effect of financial flows on economic growth depends on the investor’s expectations.

To study the short-run and long-run effects of financial flows on economic growth, this paper considers an empirical approach based on the panel ARDL. This model makes it possible to distinguish between the short-run effect and the long-run one. This type of model is based on three estimators, namely, mean group, pooled mean group (PMG) and dynamic fixed effect.

Results confirm the existence of a long-run relationship because the adjustment coefficient (error correction parameter) is negative and statistically significant. This paper finds that the PMG estimator is more consistent and more efficient. In the short-run, foreign direct investment do negatively affect economic growth, the effect is no significant in the long-run. On the other hand, the effect of remittances on economic growth is significant in the short-run. However, it is no significant in the long-run. Finally, the results suggest that the effect of official development assistance on economic growth is insignificant; both in the long-run and in the short-run.

To study the interaction between financial flows and economic growth, some empirical methodology are used such as the dynamic panel data and the autoregressive vector (VAR) model. In this study, we apply the panel ARDL model to analyze the short-run and the long-run effect for each financial flow on economic growth. The objective is to study the heterogeneity on dynamic adjustment in the short-term and long-term.

This research aims to fill the research gaps regarding customer preferences for digitalisation to create value for retailers and customers, as well as focus on retail change and shopping behaviour in grocery retail stores in the emerging market.

This paper contributes to the research in this area by evaluating customers' and retailers' attitudes towards digital transformation in retailing through interviews. Methodologically, 200 questionnaires were gathered, and data were analysed with the partial least squared structural equation modelling method.

The findings of this study reveal that the effect of digital transformation in the retail industry will be more apparent in an emerging market.

The paper's originality consists in understanding the future retail structure in an emerging market. Notably, focussing on business-to-consumer businesses appears helpful in distinguishing between behavioural (buying) intention and online buying behaviour (actual usage) in an emerging market.