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The purpose of this study is shed light on the underlying forces behind entrepreneurship within a regional innovation system (RIS) in a remote rural region. The authors examine the following questions: Which are the main underlying forces behind the entrepreneurial process in a rural RIS characterized by traditionally low-tech, small-scale businesses? How can the development of a low-tech regional innovation system be conceptualized?

The design of the study is based on entrepreneurship theory. Data analysis followed practices used in phenomenography, a research approach used to analyse and identify commonalities and variations in populations' perceptions of a certain phenomenon. Data are composed using semi-structured interviews and a database composed of company information of all firms in the population.

A proactive mobilization of regional stakeholders and resources can be an important driving force behind the entrepreneurial process and generation of a rural RIS. Innovation can be generated within low-tech industries turning the rural context into an asset. An RIS in a remote rural context can be initiated and orchestrated by regional authorities, but knowledge brokering and orchestration can also be managed by networks of small-scale businesses brought together by mutual benefit and common interests.

Regional innovation systems theory is most often used to study high-tech industries. But by combining regional innovation systems with rural entrepreneurship and entrepreneurship context theory is a fruitful avenue to understand the role of rural entrepreneurship in regional development, even in remote and peripheral regions. Innovation does not need to entail high-tech international environments; it can appear as the result of efforts in low-tech industries in rural and remote environments. The authors’ findings need to be scrutinized; therefore, the authors call for more research on regional innovation systems in rural environments.

It is possible for regional authorities to orchestrate a development process through the actions of a strong regional agent but also by supporting the creation of networks of small businesses that are built on trust and common interests.

This study contributes to the literature with a new perspective to the study of entrepreneurship and of regional innovation systems. Entrepreneurship research with focus on rural contexts most often highlight limits to entrepreneurship and see entrepreneurship as “just running a business”. A perspective that starts from innovation and innovative behaviour, despite the rural context and embedded resources, helps to generate new knowledge that can enrich the understanding of entrepreneurship and also be the foundation for more precise business development policies in rural settings.

The purpose of this paper is to systematically review the history and current state of lesson study (LS) in Germany. In particular, this paper describes the development of LS over time and its stakeholders.

Conducting a systematic literature review, we searched three scientific databases and Google Scholar, examined 806 results and included 50 articles in our final sample, which we analyzed systematically.

The spread of LS in Germany can be divided into three phases, characterized by their own LS projects as well as their own ways of understanding LS. Although interest in LS has increased significantly in recent years, it is only present at a small number of schools and universities in Germany if compared internationally. Furthermore, this paper identifies the so-called learning activity curves as a tool frequently used for observation and reflection that appears to be unknown outside German-speaking countries.

This paper may act as an outline for countries without large-scale LS projects and with limited support from policymakers. The experience from Germany demonstrates the outcomes and challenges that can arise in such a situation and shows how unique LS features and proceedings have emerged.

This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?

A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.

The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.

The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.

The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?

While digital transformation holds immense promise, organizations often fail to realize its benefits. This study aims to address how policies for digital transformation benefits realization are translated into practice.

The authors apply a qualitative, comparative case study of two large, public-sector health care organizations in Sweden. Through document and interview data, the authors analyze the process of translation.

The study finds that practice variation is primarily caused by two types of decoupling: policy-practice and means-ends. Contrary to previous studies, coercion in policy compliance is not found to decrease practice variation.

The limitations primarily stem from the empirical selection of two large public health-care organizations in Sweden, affecting the study’s generalizability. Reducing practice variation is more effectively achieved through goal alignment than coercion, leading to implications for the design of governance and control.

Policymakers should, instead of focusing on control-related compliance, work to align organizational objectives and policies to decrease practice variation for successful benefits realization.

The study contributes to better benefits realization of digital transformation initiatives in health care. As such, the authors contribute to a better functioning and more transformative health care in times of increased demand and decreased supply of health-care services.

The study challenges conventional wisdom by identifying that coercion is less effective than goal alignment in reducing practice variation, thereby enhancing the understanding of policy implementation dynamics in health-care settings.

The reason for concern is the rapid decline in loans to small enterprises which is critical to their performance, compared to large businesses following the periods of banking reformations in Nigeria. Thus, the purpose of this paper is to investigate the influence of risk perception on bank lending behaviour to small enterprises. It also investigates the impact of government intervention, consolidation and recapitalization on the relationship between risk perception and bank lending behaviour to small enterprise.

This study empirically analysed (ordinary least square) secondary data obtained from the Central Bank of Nigeria Statistical Bulletins, Annual Statement of Accounts covering the period 1992–2020.

The results show that the absence of government interventions and the presence of banking reformations have statistically negative significant effect on bank lending to small enterprises. The findings challenge the argument that generally assumes risk aversion of banks towards small enterprise lending because of small enterprise’s inability to prove their credit worthiness and consequently constraining access to finance to the sector. Instead, the results and analysis from this study found theoretical support for the variation of bank behaviour in lending to small enterprises depending on the status of wealth of the financial system.

A key lesson from this study for government concerned about promoting performance of the small enterprise sector is that regulating and enforcing lending requirements on access to debt financing of the sector is necessary if constraints in access debt finance is to be eliminated. Second, while strategies such as bank consolidation, recapitalization may help strengthen and make financially robust the banking system; it places the banks in a gain position where losses looms to them than gain.

This study challenges the argument that generally assumes risk aversion of banks towards small enterprise lending as a result of inability to prove their credit worthiness and consequently constraining access to finance to the sector. Instead, the results and analysis from this study reveal a variation in lending to small enterprises and suggests that the position of the bank in relation to a reference point influences how risk is perceived by the bank and thus impacts on their risk decision-making behaviour.

The present study distinguishes itself by pioneering an innovative framework that integrates key elements of prospect theory and the fundamental principles of electronic word of mouth (EWOM) to forecast Bitcoin/USD price fluctuations using Twitter sentiment analysis.

We utilized Twitter data as our primary data source. We meticulously collected a dataset consisting of over 3 million tweets spanning a nine-year period, from 2013 to 2022, covering a total of 3,215 days with an average daily tweet count of 1,000. The tweets were identified by utilizing the “bitcoin” and/or “btc” keywords through the snscrape python library. Diverging from conventional approaches, we introduce four distinct variables, encompassing normalized positive and negative sentiment scores as well as sentiment variance. These refinements markedly enhance sentiment analysis within the sphere of financial risk management.

Our findings highlight the substantial impact of negative sentiments in driving Bitcoin price declines, in contrast to the role of positive sentiments in facilitating price upswings. These results underscore the critical importance of continuous, real-time monitoring of negative sentiment shifts within the cryptocurrency market.

Our study holds substantial significance for both risk managers and investors, providing a crucial tool for well-informed decision-making in the cryptocurrency market. The implications drawn from our study hold notable relevance for financial risk management.

We present an innovative framework combining prospect theory and core principles of EWOM to predict Bitcoin price fluctuations through analysis of Twitter sentiment. Unlike conventional methods, we incorporate distinct positive and negative sentiment scores instead of relying solely on a single compound score. Notably, our pioneering sentiment analysis framework dissects sentiment into separate positive and negative components, advancing our comprehension of market sentiment dynamics. Furthermore, it equips financial institutions and investors with a more detailed and actionable insight into the risks associated not only with Bitcoin but also with other assets influenced by sentiment-driven market dynamics.

This paper aims to conduct a systematic review of the literature on the quality of integrated reports (IR) and highlight the gaps in the existing research to provide directions and suggestions for future research.

This study was conducted through a systematic literature review using content analysis based on 40 papers from the Scopus, Web of Science and EBSCOhost databases on IR quality. While reading the full-text papers, the authors found six additional papers referenced by the literature being reviewed that were relevant to IR quality. Thus, there were 46 papers in the final review. The analysis begins with the definition and dimension of IR quality and theoretical lenses. Furthermore, this study outlines constructs or variables used in the previous literature.

The authors found that most studies used the quantitative method (41 papers or 89%). Five papers in the literature used qualitative methods (11%). Most researchers (34 papers or 72%) defined IR quality as consistent with the International Integrated Reporting Council framework, specifically the eight content elements. In particular, with the constructs that make up the quality of the IR, variations between researchers were found. Furthermore, there were some gaps that could be the directions for future research.

The literature that provides academic knowledge about IR quality is still limited, and research on IR is still growing. The literature review conducted by this study can provide an overview of the current research positions on the quality of IR and directions for future research in this area.

This study intends to show corporate executives a framework demonstrating the quality of corporate reporting. It can impact not only investors as a specific stakeholder group but also other stakeholder groups.

To the best of the authors’ knowledge, this study is the first literature review to examine the quality of IR, thus providing a map of current research to suggest directions for future research. Most of the previous literature reviews have been focused on integrated reporting (IR) in general and not quality.

Microribbon with meander type based on giant magnetoimpedance (GMI) effect has become a research hot spot due to their higher sensitivity and spatial resolution. The purpose of this paper is to further optimize the line spacing to improve the performance of meanders for sensor application.

The model of GMI effect of microribbon with meander type is established. The effect of line spacing (Ls) on GMI behavior in meanders is analyzed systematically.

Comparison of theory and experiment indicates that decreasing the line spacing increases the negative mutual inductance and a consequent increase in the GMI effect. The maximum value of the GMI ratio increases from 69% to 91.8% (simulation results) and 16.9% to 51.4% (experimental results) when the line spacing is reduced from 400 to 50 µm. The contribution of line spacing versus line width to the GMI ratio of microribbon with meander type was contrasted. This behavior of the GMI ratio is dominated by the overall negative contribution of the mutual inductance.

This paper explores the effect of line spacing on the GMI ratio of meander type by comparing the simulation results with the experimental results. The superior line spacing is found in the identical sensing area. The findings will contribute to the design of high-performance micropatterned ribbon with meander-type GMI sensors and the establishment of a ribbon-based magnetic-sensitive biosensing system.

Given the relevance of female directors in the governance of any firm, this paper aims to examine their effect on firms’ financial performance by investigating their general impact and segregating the same into different subgroups based on Kanter’s theory.

To achieve the purpose, this study selects a sample of the top 100 listed Indian firms for the period of 2014–2018 and gathers the data pertaining to the variables under consideration from the respective firms’ annual report and corporate database Capitaline Plus. For undertaking the investigation, the authors have segregated the sample into three groups, i.e. firms with boards having less than 10% of female directors are called skewed boards; firms with boards having female directors that range from 10% to 20% are called as tilted board; and firms with boards having sizable representation of female directors of above 20%. To examine the performance impact of overall female directors and their different subgroups, the authors have used a generalized estimating equation model. For the robustness test, the authors have used the fixed-effect model.

The authors find a significant positive impact of the overall percentage of female directors on the financial performance of firms. Additionally, the results indicate that boards with a titled group of female directors and boards with a sizable representation of female directors significantly positively impact firms’ performance. However, the authors fail to extricate any significant performance impact of boards with a skewed group of female directors.

First, the study reveals that despite prevailing nepotism in India, female directors, owing to their core characteristics, can create a favorable perception of firms in the market. Second, it also works as an eye-opener for regulators by revealing the minimum threshold for female directors that a board should have to exploit the benefits of a gender quota rather than mere compliance with the requirements of the Companies Act, 2013. Third, it implies that more gender-diverse boards can improve a firm’s financial performance only if female directors range between the thresholds of 10% to 20%. Finally, the finding is significant for changing the business culture in India, where institutions are traditionally less supportive of women than in other emerging countries.

Departing from existing studies, which provide evidence on the performance impact of the overall percentage of female directors, the study unveils the differential impact of female directors on firms’ financial performance depending on their level of representation on the board. To the best of the authors’ knowledge, this is the first study in the context of an emerging market to test Kanter’s theory.

Although governments have used social media platforms to interact with the public in an attempt to minimize anxiety and provide a forum for public discussion during the pandemic, governments require sufficient crisis communication skills to engage citizens in taking appropriate action effectively. This study aims to examine how the National Health Commission of China (NHCC) has used TikTok, the leading short video–based platform, to facilitate public engagement during COVID-19.

Building upon dual process theories, this study integrates the activation of information exposure, prosocial interaction theory and social sharing of emotion theory to explore how public engagement is related to message sensation value (MSV), media character, content theme and emotional valence. A total of 354 TikTok videos posted by NHCC were collected during the pandemic to explore the determinants of public engagement in crises.

The findings demonstrate that MSV negatively predicts public engagement with government TikTok, but that instructional information increases engagement. The presence of celebrities and health-care professionals negatively affects public engagement with government TikTok accounts. In addition, emotional valence serves a moderating role between MSV, media characters and public engagement.

Government agencies must be fully aware of the different combinations of MSV and emotion use in the video title when releasing crisis-related videos. Government agencies can also leverage media characters – health professionals in particular – to enhance public engagement. Government agencies are encouraged to solicit public demand for the specific content of instructing information through data mining techniques.