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The dynamics of the competitive performance of the small medium firms is an evolving field of research in the developing countries like India. The influence of the innovation on the competitive performance of the firms is still an evolving area in India. This paper aims to explore the influence of the innovation on the competitive performance. The study is based upon the agro-food processing industry of the Jammu and Kashmir state of India.

The paper is based upon the exploratory design. It uses quantitative as well as qualitative method for the firm level analysis of competitiveness. The aggregate index method has been used to construct the innovation competence and total competitive performance index. The regression analysis is used for describing the model based upon the primary data.

The results of the study provide for a significant relationship between the innovation competence and firm level competitiveness. It describes the position of the agro-food processing firms under study with respect to the innovation competence index score and total competitiveness performance index.

The paper provides for the managerial implications of strategically incubating the innovation-based competence for the firms in specific geographical areas. The policy implications in terms of developing specific clusters and incubators for incremental and radical innovations can be derived, in regional economies.

The paper discusses the issue of interaction of innovation competence and firm level competitiveness of the agro-food processing industry, which is dynamic, specifically in the developing states. The paper discussed unique methodology of using aggregate index method for defining the innovation competence and competitiveness for the firms where the consistency of data is a major issue for such a complex phenomenon.

This study aims to empirically analyze the asset allocation capabilities of Outsourced Chief Investment Officers (OCIOs) in Korea. The empirical analysis used data from 35 funds that were evaluated by the Ministry of Strategy and Finance from 2012 to 2020. The results of the analysis are summarized as follows. First, this study found that funds that adopted OCIO improved their asset allocation performance. Second, the sensitivity between risk-taking and performance decreased for funds that adopted OCIO. Third, it is found that OCIO adoption improves a fund's asset management execution (tactical capabilities). This study has methodological limitations in which the methodology used in this study is not based on theoretical prior research, but on practical applications. However, considering the need to clearly analyze the capabilities of OCIO and the timeliness of the topic, this study is valuable and can provide meaningful information to funders who are considering adopting OCIO in the future.

This paper aims to improve the delimitation of plant growth stages in the context of weather index insurance design. We propose a data-driven phase division that minimizes estimation errors in the weather-yield relationship and investigate whether it can substitute an expert-based determination of plant growth phases. We combine this procedure with various statistical and machine learning estimation methods and compare their performance.

Using the example of winter barley, we divide the complete growth cycle into four sub-phases based on phenology reports and expert instructions and evaluate all combinations of start and end points of the various growth stages by their estimation errors of the respective yield models. Some of the most commonly used statistical and machine learning methods are employed to model the weather-yield relationship with each selected method we applied.

Our results confirm that the fit of crop-yield models can be improved by disaggregation of the vegetation period. Moreover, we find that the data-driven approach leads to similar division points as the expert-based approach. Regarding the statistical model, in terms of yield model prediction accuracy, Support Vector Machine ranks first and Polynomial Regression last; however, the performance across different methods exhibits only minor differences.

This research addresses the challenge of separating plant growth stages when phenology information is unavailable. Moreover, it evaluates the performance of statistical and machine learning methods in the context of crop yield prediction. The suggested phase-division in conjunction with advanced statistical methods offers promising avenues for improving weather index insurance design.

This study introduces the Digital Maturity Assessment Model (DMAM), a model tailored to assess the digital maturity of SMEs, tracing its development from addressing business challenges to establishing a comparative analysis framework grounded in Resource Dependence Theory (RDT).

DMAM is based on positivist philosophy and objectivist epistemology, supported by Design Science Research (DSR) and Capability Maturity Model Integration (CMMI). The methodology involves iterative development, from problem identification to creating a practical solution for assessing SMEs' digital maturity and guiding digitalization efforts.

DMAM offers a clear and specific methodology, distinguishing itself by addressing the unique needs of SMEs, particularly resource-dependent ones. The model’s development fills critical gaps in existing literature and provides a practical artifact for SMEs' digitalization.

DMAM is original in its focus on the specific needs of resource-dependent SMEs, offering actionable recommendations and addressing shortcomings in existing models. It serves as a foundational framework for SMEs' digital transformation, making a significant contribution to the digital maturity assessment literature.

With the recognition that generating economic growth is not the same as sustaining it, the challenge to catch-up and growth literature is discerning between these processes. Recent research suggests that the decline in the frequency of “shrinking” episodes is more important for long-term development than higher growth rates. By using a framework centred around social capabilities, this study aims to investigate the effects of income inequality and poverty on economic shrinking frequency, as opposed to previous literature that has exclusively had a growth focus. The aim is to investigate how and why some societies might be more resilient to economic shrinking.

The research is a quantitative study, and the authors build a longitudinal data set including 23 developing countries throughout 42 years to test the paper’s purpose. This study uses country and period fixed-effects specifications as well as cross-sectional graphical representations to investigate the relationship between proxies of economic inclusivity and the frequency of shrinking episodes.

The authors demonstrate that while inclusive societies are more resilient to shrinking overall, it is changes in poverty levels, but not changes in income inequality, that appear to be correlated with economic shrinking frequency. Inequality, while still an important element to explain countries’ growth potential as an initial condition, does not seem to make the sample more resilient to shrinking. The authors conclude that the mechanisms in which poverty and inequality are correlated with the catch-up process must run through different channels. Ultimately, processes that explain growth may intersect but not always overlap with the ones that explain resilience to shrinking.

The need for inclusive growth in long-term development has been championed for decades, yet inclusion has seldom been explored from the shrinking perspective. Though poverty reduction is already an important mainstream political objective, this paper differentiates itself by providing an alternate viewpoint of why this is important. Income inequality could have more of an economic growth limiting effect, while poverty reduction could be required to build resilience to economic shrinking. Developing countries will need both growth and resilience to shrinking, to catch-up with higher-income economies, which policymakers might need to balance carefully.

The purpose of this paper is to test the relationship between innovation performance and innovation spillover effects, innovation inputs, innovation outputs and industrial effects.

The analysis framework including variables such as innovation spillover effect, innovation input, innovation output and industrial effect was constructed. Through the investigation and analysis of the innovation activities of China’s GEM listed companies in 2014–2016, the innovation performance and the above factors were tested.

The research shows that enterprise performance has a significant positive correlation with innovation input and innovation output, but there is no significant correlation or even negative correlation with innovation environment and industry background such as government support and innovation opportunities, and the spillover effect is significant. The negative correlation is also negatively correlated with innovative human capital investment, company age and company Q.

Innovation is the real source of economic growth, and industrial innovation is the system integration of technological innovation, product innovation, market innovation, etc., which is the basic determinant of national competitiveness.

This article examines the mechanisms through which big data analytics capabilities (BDAC) contribute to creating sustainable value and analyzes the mediating roles that supply chain management capabilities (SCMC), as well as circular economy practices (CEP), play through their impact on sustainable performance.

Following a literature review, a serial mediation model is presented. Hypotheses regarding direct and mediating relationships are tested to determine their potential for sustainability impact and circularity. Partial least squares structural equation modeling (PLS-SEM) has been applied for causal and predictive purposes.

The results indicate that big data analytics capabilities do not have a direct positive impact on sustainable performance but influence indirectly through SCMC and CEP.

Although some authors have addressed the associations between IT business value, supply chain (SC), and sustainability, this paper provides empirical evidence related to these relationships. Additionally, this study performs novel predictive analyses.

Cambodia's sustained and robust growth performance since the post-reform era in 1993 has been attributed to the boom in inward foreign direct investment (FDI) attracted to the country's labor-intensive industries, where it has comparative advantages. The purpose of this study is twofold. First, it aims to assess the consistency between Cambodia's revealed comparative advantage in exports and its sectoral inward FDI. Second, it examines the relationship between industry-level FDI and growth performance by accounting for heterogeneity across industries.

The paper uses descriptive methods and an industry-level dataset provided by the Council for the Development of Cambodia to elucidate the issue. Additionally, it applies instrumental variable two-stage least squares (IV-2SLS) regression to investigate the impact of industry-specific FDI on economic growth from 1994 to 2017, which also aims to address the endogeneity issue.

On the one hand, our research finds that Cambodia's FDI has been attracted to sectors in which it has a comparative advantage during the aforementioned period. On the other hand, both FDI and the comparative advantage index significantly impact economic growth in Cambodia. The greater the flow of foreign investment into sectors with comparative advantage, the stronger the impetus for growth.

This study fills a gap in the literature and contributes to a better understanding of the relationship between FDI and economic growth in Cambodia. It is the first paper to investigate the heterogeneity of industry-specific FDI and provides practical recommendations for policymakers to effectively harness foreign investments and avoid malign FDI inflows.

The purpose of this paper is to investigate the major political and economic changes in the world and the likely impact that these changes will bring to tourism and hospitality industries.

The paper adopts a geopolitical perspective on the dynamics of tourist flows, stipulating that geopolitics has a major impact on the size, structure, and direction of these flows.

The paper identifies six geopolitical drivers of tourist flows in the future, namely: the fall of the American Empire, the rise of the BRIC and the PINE countries, increased global political instability, increased importance of regional supranational organisations, greater control of the individuals on a global scale, and the greater importance and power of corporations than national governments.

The paper critically evaluates the geopolitical drivers of tourist flows, their likely future development and the impact they have on tourism.

Purpose – This research study aims to answer the question of how good is the development of the extended regency, and which shows better autonomy of development—before or after expanding. The implications of this study is to answer whether expanding a regent is truly needed to improve the economic development and welfare of the remote regions and their people. This study analyzes the autonomous state of three regencies, North Aceh, Bireuen and Lhokseumawe districts, which have expanded. The analysis takes into consideration the difference in the proportion of their regional revenues, budgeting perfomance, and economic growth as indicators of regional autonomy.

Design/Method/Approach – The data used in this research are secondary data sourced from the budget realization report and the accountability report of North Aceh, Bireuen, and Lhokseumawe districts from 2006 to 2013. The data analysis methods used in this study are the analysis of financial ratios and the comparative mean of one way anova.

Finding – The results showed a significant value or a probability value more than 0.05. Thus, the hypothesis (H1) is rejected, and therefore the hypothesis (H0) is received.

Research Impication – The implication is that there is no difference in the average of regional autonomy of North Aceh Regency, Bireuen, and Lhokseumawe districts as seen from the proportion of local revenue, budgeting perfomance, and regional growth. It means that with regard to financial performance there is no difference in the level of independence in autonomy among the three regions. The proportion of local revenue, financial permormance area, and the development of North Aceh, Bireuen, and Lhokseumawe districts demonstrate no influence on the level of independence in autonomy.