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The purpose of this paper is to identify dimensions that can influence the innovation process in justice organizations.

This study uses a qualitative approach. Data were collected through a semi-structured interview script. In all, 23 in-depth interviews were undertaken with lawyers, public defenders, judges, prosecutors and public officials from the five regions of Brazil. These data were analyzed using content analysis techniques.

The perceptions of the interviewees show that the process of innovation in justice organizations can be influenced by five dimensions: Institutional Environment (institutional level), Leadership (organizational level), Organizational Resources (organizational level), Cooperative Relations (interorganizational level) and Innovative Behavior (individual level). These dimensions may promote or restrict innovation.

The results indicate that there are growing efforts to introduce innovations designed to improve the performance and service delivery of justice organizations. However, there is resistance to innovation because these organizations are highly institutionalized and consequently seek stability and absence of change.

This study aims to identify the key enablers for the adoption of Industry 4.0 (I4.0) in the automobile industry of India, which has been severely impacted by COVID-19. Adopting I4.0 will provide organizations greater flexibility and resilience during the COVID-19 pandemic.

Based on the literature review and experts’ opinions, 21 enablers were identified. Further, contextual relationships among the identified factors and a hierarchical digraph was developed by using the total interpretive structural modelling (TISM) technique. Finally, fuzzy cross-impact matrix multiplication applied to classification (MICMAC) analysis was conducted to classify the enablers into different categories based on their dependence and driving power.

The results indicate that top management support, clarity on government policy, strategic vision on I4.0 and development of new industrial policy are the most influential factors, with the highest driving power placed at the bottom of the TISM hierarchical model. Furthermore, agile workforce, smart HR practices and IT standardization and security are identified as linkage enablers with the most driving and dependency power.

The hierarchical TISM model and fuzzy MICMAC approach provide a comprehensive understanding of the I4.0 implementation process through a visual, logical structure to the managers. It will help the researchers and practitioners understand the contextual relationship among various enablers in fostering the I4.0 adoption process and digital reorganization in the automobile industry during the COVID-19 pandemic.

This study provides a holistic TISM hierarchical framework on I4.0 adoption that will elevate the next maturity level of innovation adoption and may act as a blueprint for automobile industries during the COVID-19 pandemic.

Drawing on Weick’s sensemaking perspective, this study aims to describe how Czech social entrepreneurs shape the shared meaning of the crisis caused by the COVID-19 pandemic and what approaches to the crisis the sensemaking process leads to.

This study is based on the principles of grounded theory. Through in-depth interviews with 25 social entrepreneurs, it captures the entrepreneurs’ experience of the COVID-19 pandemic in the context of their understanding of social enterprise identity. Interviews with experts in the field of social entrepreneurship were also conducted to help achieve a deeper analysis of the entrepreneurial cases.

Results of research show that despite the obstacles, most social entrepreneurs arrive at a positive redescription of the crisis. Enterprises not affected by the pandemic adopt a conventional approach. The most vulnerable enterprises are paralyzed and wait with uncertainty for future developments in their enterprise’s situation.

As knowledge of vulnerabilities is a key prerequisite for crisis prevention, this research can serve as a useful material for business incubators and other institutions that provide mentoring and expertise to start-up social entrepreneurs including focus on crisis management implementation.

This study complements the theory of crisis sensemaking with the level of social entrepreneurship, which is characterized by a dichotomy of social and business goals that results in a specific shared meaning of identity which is tied to perceptions of vulnerabilities. This study describes the influence of perceived identity on coping with a crisis.

This study aims to analyze the volatility spillover effects of crude oil, gold price, interest rate (yield) and the exchange rate (USD (United States Dollar)/INR (Indian National Rupee)) on inflation volatility in India.

This study uses the multivariate Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models (Baba, Engle, Kraft and Kroner [BEKK]-GARCH and dynamic conditional correlation [DCC]-GARCH) to examine the volatility spillover effect of macroeconomic indicators and strategic commodities on inflation in India. The monthly data are collected from January 2000 till December 2020 for the crude oil price, gold price, interest rate (5-year Indian bond yield), exchange rate (USD/INR) and inflation (wholesale price index [WPI] and consumer price index [CPI]).

In BEKK-GARCH, the results reveal that crude oil price volatility has a long time spillover effect on inflation (WPI). Furthermore, no significant short-term volatility effect exists from crude oil market to inflation (WPI). However, the short-term volatility effect exists from crude oil to inflation while considering CPI as inflation. Gold price volatility has a bidirectional and negative spillover effect on inflation in the case of WPI. However, there is no price volatility spillover effect from gold to inflation in the case of CPI. The price volatility in the exchange rate also has a negative spillover effect on inflation (but only on CPI). Furthermore, volatility of interest rates has no spillover effect on inflation in WPI or CPI. In DCC-GARCH, a short-term volatility impact from all four macroeconomic indicators to inflation is found. Only crude oil and exchange rate have long-term volatility effect on inflation (CPI).

In an economy, inflation management is an essential task. The findings of the current study can be beneficial in this endeavor. The knowledge of the volatility spillover effect of all the four markets undertaken in the study can be significantly helpful in inflation management, especially for inflation-targeting policy.

It is observed that no other study has addressed this issue. We do not find any other research which studies the volatility spillover effect of gold, crude oil, interest rate and exchange rate on the inflation volatility. The current study is novel with a significant contribution to the vast knowledge in this context.

The purpose of this study is to develop the dictionary with grammar and multiword structure has to be used in conjunction with sentiment analysis to investigate the relationship between financial news and stock market volatility.

An algorithm has been developed for calculating the sentiment orientation and score of data with added information, and the results of calculation have been integrated to construct an empirical model for calculating stock market volatility.

The experimental results reveal a statistically significant relationship between financial news and stock market volatility. Moreover, positive (negative) news is found to be positively (negatively) correlated with positive stock returns, and the score of added information of the news is positively correlated with stock returns. Model verification and stock market volatility predictions are verified over four time periods (monthly, quarterly, semiannually and annually). The results show that the prediction accuracy of the models approaches 66% and stock market volatility with a particular trend-predicting effect in specific periods by using moving window evaluation.

Only one news source is used and the research period is only two years; thus, future studies should incorporate several data sources and use a longer period to conduct a more in-depth analysis.

Understanding trends in stock market volatility can decrease risk and increase profit from investment. Therefore, individuals or businesses can feasibly engage in investment activities for profit by understanding volatility trends in capital markets.

The ability to exploit textual information could potentially increase the quality of the data. Few scholars have applied sentiment analysis in investigating interdisciplinary topics that cover information management technology, accounting and finance. Furthermore, few studies have provided support for structured and unstructured data. In this paper, the efficiency of providing the algorithm, the model and the trend in stock market volatility has been demonstrated.

Internal (e.g. firm performance, internal stakeholders) and external pressures (e.g. globalisation, technology, corporate scandals) have intensified calls for corporate governance reforms across varieties of capitalism. Yet, corporate governance practices among developing economies remain problematic. Drawing insights from Africa’s largest economy (Nigeria) and relying on the resource dependence theorisation, this study aims to address two questions – what are the prerequisites for effective reforms; and what reforms yield robust corporate governance?

This study adopts a qualitative methodology comprising semi-structured interviews with 21 executives in publicly listed Nigerian firms. The interviews were analysed using the content analysis technique.

This study proposes two sequential reforms (i.e. the upstream and downstream). The upstream factors highlight the preconditions that support corporate governance reforms, i.e. government commitment and enabling environment, while the downstream reforms combine elements of awareness and regulation to proffer robust corporate governance interventions.

This research further stresses the need to consider a bottom-up approach to corporate governance in place of the dominant top-down strategy. This strategy allows agents to participate actively in corporate governance policy-making rather than a top-down model, which imposes corporate governance on agents.

The purpose of this paper is to examine how employee voice in small and medium enterprises (SMEs) is shaped by national culture. Specifically, the paper explores the relationship between national culture and organisational norms and signals. Furthermore, it explores the impact of such norms on employee voice behaviours. The paper chooses to address these issues in the SME context, in three countries with divergent cultural dimensions.

The authors use Kwon and Farndale’s (2020) typology as our “a priori” framework to explore the influence of national cultural values and cultural tightness on SME organisation norms, signals and employee voice behaviours. Our study uses qualitative data gathered through in-depth interviews with SME employees in England, Nigeria and Thailand.

The results from our interviews are presented thematically. The data illustrates how the cultural dimensions identified by Kwon and Farndale (2020) can have an influence on organisational voice norms. The dimensions are power distance, uncertainty avoidance, in-group collectivism, performance orientation, assertiveness and cultural tightness.

Historically, the impact of national culture as a macro factor on voice has been largely ignored by academic research. Studies in non-western contexts are especially rare. This paper derives its originality by offering unique insights into the culture–voice relationship from both western and non-western perspectives. This provides an international, cross-cultural, comparative dimension to our study. This research includes findings from under-researched settings in Nigeria and Thailand.

This paper investigates the lean enabling human capacities and develops a framework integrating individual, organisational and environmental level strategies to build human capacities for successful lean implementation of small and medium contractors (SMCs) in Sri Lanka.

An interpretivism stance is adopted, and a qualitative research approach is used. The data collection technique adopted is semi-structured interviews. In total, 24 experts with experience in lean implementation of SMCs were interviewed, and data were analysed through code based content analysis using NVivo10.

Team working skills, critical thinking, leadership, communication skills, work ethics, knowledge and positive attitudes were identified as lean enabling human capacities for SMCs. The framework developed in this study provides individual, organisational and environmental level strategies that can be used to build human capacities necessary for enabling lean in construction SMCs.

The study will be beneficial to construction SMCs, academics, researchers and government institutions in developing countries, which share socio-economic, demographic or cultural traits similar to Sri Lanka.

A novel lean enabling human capacity building framework is developed with the strategies required for building those capacities in order to accelerate the lean implementation in construction SMCs. This contributes to the body of knowledge as it uncovers individual, organisational and environmental level strategies for enabling lean through human capacity building in Sri Lankan SMCs.

The purpose of this paper is to examine the reliability and validity of the knowledge management assessment instrument (KMAI) developed by Lawson (2003) that consists of 24 items.

The study involved 225 research scholars and 225 faculties’ members from nine higher educational institutions. The respondents were required to respond to a five-point Likert scale from strongly agree to strongly disagree. The collected data were then analyzed using the SPSS 18.0 and AMOS 18.0 software packages. An exploratory factor analysis was conducted earlier than performing a confirmatory factor analysis.

All constructs revealed the acceptable internal consistency reliability. A good model fit was found for the measurement model using several fit index tests like CMINDF, TLI, GFI AGFI, CFI and RMSEA. The findings showed that all fit indices criteria were accomplished. It also showed the acceptable reliability and construct validity.

KMAI was examined using confirmatory factor analysis only. A large sample size and sample area can be used.

This research paper is an endeavor to explore only the reliability and validity of the KMAI. Thus all the three dimensions, namely, “knowledge application”, “knowledge acquisition and creation” and “knowledge storing and sharing” proved out to be reliable and validate when it will be tested in case of any Indian higher educational institutions.

The main contributions of this study is that all the factors have good acceptable reliability value; each factor can be measured individually depending on the nature of the research.

The main purpose of this paper is to analyse the influence of capital efficiency on the economic growth of Bangladesh using the Harrod-Domar (H-D) model.

We use annual data from 1980 to 2019 for this paper. Three steps are taken in the data analysis. First, to check the existence of a unit root, we use the augmented Dickey-Fuller (ADF) test and to determine co-integration among the variables, we use the Johansen-Juselius co-integration test. Next, for long-run estimation, we use the dynamic ordinary least square (DOLS) estimator. The sensitivity of the long-run estimations is further checked by the fully modified OLS (FMOLS) and autoregressive distributed lag (ARDL) estimators. Lastly, we use the Granger causality test to determine the long-run causality among the variables.

The long-run co-integration test validates the co-integrating relationship among the variables. DOLS estimations reveal that the economic growth of Bangladesh is negatively associated with the incremental capital output ratio (ICOR), validating the notion that capital efficiency matters for achieving higher economic growth. On average, an increase in ICOR by a unit tends to reduce economic growth in the long term by 0.75 percent. Our results also reveal no significant relationship between savings and economic growth when the model is extended. Finally, causality results indicate unidirectional causality between ICOR and economic growth.

Based on the results obtained, we argue that the enhancement of capital productivity could bring efficiency because ICOR is an inverse of capital productivity. Since Bangladesh’s capital productivity is considerably low compared with other neighbouring countries, it is suggested that firms should gradually move towards technological advancement and enhance economies of scale, etc. in the long run. Moreover, policies in favour of continuous skill development programmes could be highly effective in increasing capital productivity given that capital follows a vintage structure.

This is the first paper to analyse the economic growth pattern of Bangladesh using the traditional H-D model by incorporating variables such as savings and ICOR and also by relaxing the assumption of time-invariant (i.e. fixed) data of the variables. Moreover, this paper extends the traditional H-D empirical model by introducing key indicators and time breaks for Bangladesh’s economy through a stepwise regression process.