Search results

This study examines the roles of cross-sectional dependence, asymmetric structure and country-to-country policy variations in the inflation-poverty reduction causal nexus in selected sub-Saharan African (SSA) countries from 1981 to 2019.

To account for cross-sectional dependence, heterogeneity and policy variations across countries in the inflation-poverty reduction causal nexus, this study uses robust Hatemi-J data decomposition procedures and a battery of second-generation techniques. These techniques include cross-sectional dependency tests, panel unit root tests, slope homogeneity tests and the Dumitrescu-Hurlin panel Granger non-causality approach.

Unlike existing studies, the panel and country-specific findings exhibit several dimensions of asymmetric causality in the inflation-poverty nexus. Positive inflationary shocks Granger-causes poverty reduction through investment and employment opportunities that benefit the impoverished in SSA. These findings align with country-specific analyses of Botswana, Cameroon, Gabon, Mauritania, South Africa and Togo. Also, a decline in poverty causes inflation to increase in the Congo Republic, Madagascar, Nigeria, Senegal and Togo. All panel and country-specific analyses reveal at least one dimension of asymmetric causality or another.

All stakeholders and policymakers must pay adequate attention to issues of asymmetric structures, nonlinearities and country-to-country policy variations to address country-specific issues and the socioeconomic problems in the probable causal nexus between the high incidence of extreme poverty and double-digit inflation rates in most SSA countries.

Studies on the inflation-poverty nexus are not uncommon in economic literature. Most existing studies focus on inflation’s effect on poverty. Existing studies that examine the inflation-poverty causal relationship covertly assume no asymmetric structure and nonlinearity. Also, the issues of cross-sectional dependence and heterogeneity are unexplored in the causal link in existing studies. All panel studies covertly impose homogeneous policies on countries in the causality. This study relaxes this supposition by allowing policies to vary across countries in the panel framework. Thus, this study makes three-dimensional contributions to increasing understanding of the inflation-poverty nexus.

This study aims to examine the entrepreneurship profiles of migrants and refugees relying on a neo-configurational approach that increases understanding of causal complexity, equifinality and causal asymmetry patterns to high entrepreneurial intentions in the two groups.

Using a fuzzy set qualitative comparative analysis method, the authors analysed 52 respondents – migrants and refugees. The findings show the existence of equifinality in which different configurations can lead to high and low entrepreneurial intentions, underlying that traumatic experiences have a major role in entrepreneurial intention. It also demonstrates that core conditions are associated with refugee’s configurations and causal asymmetry. The cross-sectional character of this research impedes the searching for a better causal relationship. The lack of studies that approach the subject of refugees makes it challenging to develop a robust theory in this sense.

The paper highlights five main configurations – two related to migrants’ profile and three related to refugees’ profile – that enable expanding the current knowledge and practices to better customize practices to increase entrepreneurial intention.

To the best of the authors’ knowledge, this is the first research using a configurational approach to explore migrant and refugee entrepreneurship intention profiles.

The purpose of this paper is to lay out the data competence maturity model (DCMM) and discuss how the application of the model can serve as a foundation for a measured and deliberate use of data in secondary education.

Although the model is new, its implications, and its application are derived from key findings and best practices from the software development, data analytics and secondary education performance literature. These principles can guide educators to better manage student and operational outcomes. This work builds and applies the DCMM model to secondary education.

The conceptual model reveals significant opportunities to improve data-driven decision making in schools and local education agencies (LEAs). Moving past the first and second stages of the data competency maturity model should allow educators to better incorporate data into the regular decision-making process.

Moving up the DCMM to better integrate data into their decision-making process has the potential to produce profound improvements for schools and LEAs. Data science is about making better decisions. Understanding the path laid out in the DCMM to helping an organization move to a more mature data-driven decision-making process will help improve both student and operational outcomes.

This paper brings a new concept, the DCMM, to the educational literature and discusses how these principles can be applied to improve decision making by integrating them into their decision-making process and trying to help the organization mature within this framework.

This paper aims to identify the interaction of different intervention strategies implemented in Malaysia towards flattening the curve of COVID-19 cases. Since the outbreak of COVID-19, many approaches were adopted and implemented by the Malaysian government. Some strategies gained quick wins but with negative unintended consequences after execution, whereas other strategies were slow to take effect. Learning from the previous strategies is pivotal to avoid repeating mistakes.

This paper presents the cause, effect of and connection among the implemented COVID-19 intervention strategies using systems thinking through the development of a causal loop diagram. It enables the visualisation of how each implemented strategy interacted with each other and collectively decreased or increased the spread of COVID-19.

The results of this study suggested that it is not only essential to control the spread of COVID-19, but also to prevent the transmission of the virus. The Malaysian experience has demonstrated that both control and preventive strategies need to be in a state of equilibrium. Focusing only on one spectrum will throw off the balance, leaving COVID-19 infection to escalate rapidly.

The developed feedback loops provided policy makers with the understanding of the merits, pitfalls and dynamics of prior implemented intervention strategies before devising other effective intervention strategies to defuse the spread of COVID-19 and prepare the nation for recovery.

Following the lead of neighboring fields such as strategy and organization studies, entrepreneurship is gradually joining in the adoption of a practice perspective. Entrepreneurship as practice (EaP) is thus a nascent domain of investigation where the methodological debate is still unsettled and very fluid. In this paper, the authors contribute to this debate with a focus on family entrepreneurship.

The authors develop a conceptual paper to discuss what it entails to look at family entrepreneurship through a practice lens and why it is fruitful. Moreover, the authors propose a research strategy novel to the field through which such investigation can be pursued, namely process tracing, and examine its inferential logic.

Process tracing is a strategy of data analysis underpinned by an ontology of causal mechanisms. The authors argue that it complements other practice methods by inferring social mechanisms from empirical evidence and thereby establishing a connection between praxis, practices and practitioners.

Process tracing helps the articulation of an “integrated model” of practice that relates praxis, practices and practitioners to the outcome they jointly produce. By enabling the assessment of impact, process tracing helps providing prima facie evidentiary grounds for policy action and intervention.

Process tracing affinity with the practice perspective has been so far acknowledged only to a limited extent in the social sciences, and it is, in fact, a novel research strategy for the family entrepreneurship field.

This paper aims to investigate the relationships amongst career patterns, neutrality of the state civil apparatus, and organizational performance of the local government in South Konawe District, Southeast Sulawesi Province in Indonesia.

Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to investigate the relationships between variables through direct and indirect influence testing.

The findings reveal that career patterns influence neutrality and organizational performance. Neutrality of the state civil apparatus in politics mediates career patterns and local government organizational performance. The findings indicate that, first, promotions most significantly influence the organization’s neutrality and performance. Second, demotions have the least influence on the organization’s robustness and performance.

This paper is among the first to examine the relationships amongst career patterns, neutrality, and organizational performance. Recommendations are provided to improve neutrality and organizational performance, that is, the need to increase promotions and reduce demotions.

This study has two objectives. The first aim is to ascertain whether innovation and market orientation have direct, indirect, and causal effects on customer service. The second objective is to ascertain whether market orientation has a moderating effect on the relationship between innovation and customer service. This research follows three distinct methodologies. The first approach uses Cronbach’s alpha coefficient in order to check reliability while an exploratory factor analysis and a confirmatory factory analysis ascertain validity. The second method uses the analysis of structural equation models to test a causal link between variables. The third methodology uses a moderated regression analysis to verify the moderating effects. As our analysis results show, intelligence generation and intelligence dissemination have a moderating effect on the relationship between innovation and flexibility. These results can be interpreted as follows: firstly, customs clearance firms can provide superior service to customers if they strive to understand customer needs and provide them with flexible service at the same time. Secondly, these firms can enhance their flexibility of service in all departments though innovation and information sharing acquired from the market.

Though logistics security only took care of trading phase in the past, many countries in the world have begun to introduce logistics security system as its coverage has been extended from production stage to delivery at the final destination. Logistics security system has become indispensable element for global corporations involved in international trading and studies on logistics security keep going on. Most of the studies, however, are focused on discussion of system, cost and influence of logistics security and few of them have been specifically dealing with substantial effectiveness thereof. This study developed the models of supply chain security activities and their outcome by means of using Balanced Scorecard (BCS) which is a well known performance indicator to identify relationship between supply chain security activities and their accomplishment. In this study we have presented 8 supply chain frameworks, human resources management, information system management, facilities/freight management, security process, crisis management capability, relationship with partners, sharing of logistics information and logistics security accomplishment, with reference to standards of C-TPAT and AEO based on WCO framework, 10 supply chain security capabilities. This study further indicates that relationship with partners has more effect on logistics security accomplishment than sharing of logistic information. Just as relationship between corporations in chain of supply and sharing of information among them are important elements in management of supply chain, relationship with partners and sharing of logistic information will have positive effect on supply chain security accomplishment and raise its effectiveness.

The purpose of this study is to analyze the performance of indigenous innovation in developing countries in the era of trade liberalization. It analyzes indigenous innovation from research and development (R&D) investments to innovation output and its effect on economic growth.

The sample for this study includes 20 middle-income countries across five continents for the period between 1994 and 2018. The study employs the Crepon Duguet and Mairessec CDM model in a panel data setting to do a multistage analysis of the innovation process. A vector error correction model VECM is employed to test for Granger causality between the variables investigated.

The results show that imports and foreign direct investments (FDI) have generally have short-run and long-run causal effects on domestic R&D investments. In regions where imports and FDI do not have individual causal effects on innovation output, a joint increase in each of them and R&D have both short-run and long-run causal effects. Indigenous innovation is a significant contributor to economic growth when a country can produce and export novel products.

The sample is only limited to developing economies, and due to the unavailability of data, only 20 countries were captured.

Imported products and FDI are critical to the innovation drive when such activities are targeted at enhancing indigenous innovation from R&D to the production of new products. Hence, policy formulation should encourage the absorption of foreign technologies that serve as inputs to indigenous innovation.

This paper focuses specifically on indigenous innovation and analyses the influence of foreign technologies in this effort. It tests the moderating roles of imports and FDI in the relationship between R&D and innovation output, concluding that both variables enhance the effect of R&D on innovation output.

The paper aims to analyse the social responsibility concept and to explore its role in the implementation process of the tourism sustainability concept. The intention is to explore the way in which the social responsibility concept is implemented in the tourism and analyse how it contributes to its sustainability.

In this interpretivist research, the authors implemented a qualitative strategy using the following methods: content, critical and comparative analyses of the results reported in available scientific studies, categorization, causal analysis and mental mapping. The authors identified 14 thematic categories of research on the tourism social responsibility. For the causal description, the authors used driving force, pressure, state, impact, response (DPSIR) method.

The results include identification of the categories of the research topics concerning tourism social responsibility as well as categories of the approaches to the implementation of the social responsibility into the practice of the tourism sector. The causal description of this implementation process is elaborated in the form of the DPSIR model. The created mental map shows the specific facets of the social responsibility concept applied to the diverse tourism subsectors.

The main contribution lies in basic overview of the conceptual (theoretical) and instrumental (practical) base for implementation of the social responsibility concept into the tourism, providing in this way a critical analysis of examples of the social responsibility practice in the key tourism subsectors. The examination of the causal analyses in the form of DPSIR model as well as employment of the content analyses in the form of mental map represent innovative approach to the tourism responsibility research.