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The effect of dynamic capabilities on operational excellence and the moderating effect of environmental dynamism on the relationship between operational excellence and dynamic capabilities in the apparel industry in Sri Lanka were investigated while developing new psychometric scales to assess operational excellence and dynamic capacities constructs.

We followed the exploratory sequential research design with a mixed-method research approach, aligning with the pragmatic research philosophy. Thus, both qualitative and quantitative research methods were followed.

Dynamic capabilities positively affect operational excellence, and environmental dynamism moderates the relationship between operational excellence and dynamic capabilities in the apparel industry in Sri Lanka such that when a higher environmental dynamism exists, a weaker positive relationship exists between dynamic capabilities and operational excellence. The two main dimensions of the operational excellence construct are continuous improvement of sustainable operational performance and sustainable competitive advantages. It empirically confirmed that sensing, seizing and reconfiguring capabilities are the three main dimensions of the dynamic capabilities construct.

This study was limited to the apparel industry in Sri Lanka. This research phenomenon should be explored in other industrial sectors worldwide to generalize the findings. The practitioners in the apparel sector may improve the organizational dynamic capabilities to achieve operational excellence and keep a strong positive relationship between dynamic capabilities and operational excellence in a highly dynamic environment if they address out-of-family situations with out-of-the-box thinking.

We generated two new empirical findings: (1) dynamic capabilities positively affect operational excellence, and (2) environmental dynamism moderates the relationship between dynamic capabilities and operational excellence. Also, we introduced validated new scales for assessing operational excellence and dynamic capabilities.

This paper empirically investigates the relationship between financial availability and crime by measuring it across five dimensions: banking, securities, insurance, private lending and digital inclusive finance.

The study utilizes 2011–2017 data from prefecture-level cities as a representative sample. Moreover, these findings remain robust after addressing endogeneity through the use of the historical distance between cities and the railroad network as an instrumental variable.

The findings demonstrate a significant negative relationship between financial accessibility and crime rates. Heterogeneity exists in the inhibitory effect of different types of financial accessibility on crime, with banking finance exhibiting a stronger inhibitory effect compared to private lending. Areas affected by natural disasters and infectious diseases exhibit a stronger inhibitory effect of financial accessibility on crime rates, particularly in areas with severe shocks of natural disasters and epidemics. This effect is attributed to the low financing threshold and easy access to private lending, which plays a more effective role than bank finance when people face extreme risks.

There should be stricter regulations imposed on private lending markets and the introduction of more rational legislation aimed at guiding a healthy development within these markets; such measures serve as effective and complementary means for individuals from all walks of life to access credit financing.

The regulation of financial resources by the government should always prioritize ensuring the accessibility of financial policies to cater to the needs of the majority population.

This study is for the first time in an emerging economy context, the causal relationship between financial accessibility and crime. To provide a more comprehensive measure of financial accessibility in a region, this paper proposes a five-dimensional methodology.

This study examines the effect of digitalization on poverty and income inequality in developing countries. The study answers the question of whether digitalization is a way for developing countries to get out of poverty and income inequality.

The study uses data from 17 developing countries with data from 2005 to 2021. The study employs fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS), with an augmented mean group (AMG) for robustness. Digitalization, as the variable of interest, is proxied by the digitalization index (DI), constructed using principal component analysis (PCA). The dependent variables are poverty and income inequality, which are used in different models.

The evidence indicates that digitalization decreases poverty and income inequality in developing countries. These findings are justified when we use the AMG estimator, but the strength of the coefficients and significance levels are higher in the FMOLS and DOLS estimators. The results of the control variables also show that human development (LHDI), CO2 emissions and foreign direct investment (FDI) have decreasing effects on poverty and income inequality. Thus, digitalization is a good option for developing countries to get out of poverty and income inequality to achieve sustainable development goals (1&10).

This study provides rigorous empirical evidence on the effect of digitalization on poverty and income inequality in developing countries. Unlike the previous studies on developing countries, this study used a DI to proxy digitalization. In addition, the authors use FMOLS and DOLS estimators, with an AMG estimator for robustness, to provide long-run coefficients.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2023-0586

The purpose of the article is to examine the effect of life cycle stages on capital expenditures, using Borsa Istanbul-listed companies.

The panel data estimation procedure was used as the primary method to test the hypothesis. The authors used four additional analyses to check the robustness of the results. The model was tested for endogeneity using the generalized method of moments (GMM) estimation. Quantile regression was utilized for the non-parametric test of the model. In the third robustness test, the sample was divided into two using financial constraints with the Size-Age (SA) Index proposed by Hadlock and Pierce (2010). The last analysis removed the global financial crisis (GFC) years from the sample.

Borsa Istanbul-listed companies tend to invest less as they move forward in their life cycle stages. The results show that market capitalization, operating cash flow levels and leverage positively affect capital expenditure investments. The empirical evidence also revealed that cash holding levels have a negative effect on capital expenditure decisions. Robustness tests support the results.

The findings are potentially useful for investors and managers. Having the information that decreasing capital expenditures signals that the company is in the last stages of its life would be a sign for managers to improve their investment strategies to avoid getting out of business and survive. They need to find options and solutions to propel their companies back on a path of growth. Additionally, the same information could be vital for investors' investment decisions.

This paper contributes to the literature by providing evidence about the effect of life cycle stages on capital expenditures from an emerging market. To the best of the authors’ knowledge, it is the first paper to investigate empirically how moving forward in the life cycle stages affects capital expenditures in an emerging market.

Land transactions are a key indicator of urban sustainable development and urban space expansion. Therefore, this paper aims to study the spatial correlation of different types of land transactions.

Based on the big data of land micro transactions in Yangtze River Delta urban agglomeration, this paper uses the generalized forecast error variance decomposition (GFEVD) method to measure the correlation level of urban land markets. Also, social network analysis (SNA) is used to describe spatial correlation network characteristics of an urban agglomeration land market. In the meantime, the factors that influence the spatial correlation of urban land markets are investigated through a quadratic assignment procedure (QAP).

The price growth rate of urban residential land was higher than that of industrial land and commercial land. The spatial relevance of urban residential land is the highest, while the spatial relevance of the urban commercial land market is the lowest. The urban industrial land market, commercial land market and residential land market all present a typical network structure. Population distance (POD) and Engel coefficient distance (EGD) are negatively correlated with the correlation degree of the urban residential land network; traffic distance (TRD) and economic distance (ECD) are negatively correlated with the correlation degree of the urban industrial land network and commercial land network.

This paper uses a systematically-integrated series of problem-solving models to better explain the development path of urban land markets and to realize the integration of the interdisciplinary methods of geography, statistics and big data analysis.

The purpose of this study is to examine job engagement and creativity of employees in the hospitality industry of Pakistan as outcomes of empowering leadership through the mediating role of creative self-efficacy.

An electronic survey was conducted to collect data from 373 employees of food-chain restaurants in Pakistan. The data was analyzed by applying structural equation modeling (SEM) through Smart PLS 3.

Results indicated that empowering leadership has a positive association with job engagement and employee creativity in the hospitality industry. Further, creative self-efficacy has been found as mediating the relationship of empowering leadership with job engagement and employee creativity.

The study has substantial implications for the employees, managers and organizations of the hospitality industry as well as for the scholars of services industry research.

The purpose of this study is to explore the continuity and stability of the impact of accounting information quality on cash holdings, and the moderating effect of this relationship on state ownerships and local appointments.

Based on China's companies from 2011 to 2019, the authors divided cross-section and panel samples, adopted a linear and classification model and performed grouping regression.

The authors find that: first, the quality of corporate accounting information can significantly improve the level of cash holding, giving play to the strategic value effect of cash holding. But that boost is based on economies being able to solve agency problems. Second, the reduction of earnings management and the improvement of accounting information quality of NSOEs improve the level of cash holdings, while SOEs are on the contrary. Third, local appointments can play to the emotional strengths of their hometowns and play a synergistic role in this relationship, but the supervision effect of remote appointments is not obvious.

Through endogeneity and other tests, the conclusion is robust. Based on the agency and information asymmetry theory, the authors considered China's institutional and cultural factors, optimized accounting information's measurement and expanded the research boundary of the accounting field. The authors believe that applicable scenarios should be fully considered in the concluding relationship between accounting information quality and cash holdings. Enterprises should give full play to the advantages of cash holdings in strategic decision-making and financial efficiency, improve the quality of accounting information and also consider state ownerships and the differences in directors' emotions to reduce internal agency costs.

This paper aims to explore the importance of knowledge-oriented leadership in the context of business model innovation (BMI) and open innovation. This study also seeks to explore the existence of a mediating effect of absorptive capacity.

Data were collected using a survey, from the information technology industry in India. The relationships proposed in the conceptual framework were tested with structural equation modeling (SEM) using Smart partial least squares (PLS) 3.

The findings highlight a positive influence of knowledge-oriented leadership on BMI and open innovation. Results also revealed that open innovation can facilitate BMI. Additionally, findings highlighted the mediating role of absorptive capacity in these relationships.

This study suggests that businesses should employ and value leaders who can create, transform, store and use knowledge resources. Companies that employ such leaders encourage the creation and exchange of new knowledge, which consequently would lead to the successful exploration of innovative approaches. A culture of open innovation would help managers break down barriers, overcome inertia and continuously test new business models to generate revenues, increase value, enhance organizational effectiveness and ultimately gain competitive advantage.

This study is one of the first to empirically contribute to the role of knowledge-oriented leadership and BMI from the perspective of open innovation.

This study aims to evaluate the usage of partial least squares structural equation modeling (PLS-SEM) in journals related to logistics and supply chain management (LSCM).

Based on a structured literature review approach, the authors reviewed 401 articles in the field of LSCM applying PLS-SEM published in 15 major journals between 2014 and 2022. The analysis focused on reasons for using PLS-SEM, measurement model and structural model evaluation criteria, advanced analysis techniques and reporting practices.

LSCM researchers sometimes did not clarify the reasons for using PLS-SEM, such as sample size, complex models and non-normal distributions. Additionally, most articles exhibit limited use of measurement models and structural model evaluation techniques, leading to inappropriate use of assessment criteria. Furthermore, progress in the practical implementation of advanced analysis techniques is slow, and there is a need for improved transparency in reporting analysis algorithms.

This study contributes to the field of LSCM by providing clear criteria and steps for using PLS-SEM, enriching the understanding and advancement of research methodologies in this field.

The demand for power has surged in recent times and continues to increase yearly. In comparison to developed countries, the power industry’s risks, especially in piblic–private partnership (PPP) projects, are more complex and essential in developing countries. Appreciating the inter relationship among these risk factors is crucial. However, there exist no studies developing quantitative models to explain how various PPP power risk factors influence each other, especially in developing countries like Ghana. This study aims to investigate and model the relationship, the probability of occurrence and severity of impact of PPP power risk factors in Ghana.

Data were collected through ranking type questionnaire in a two-round Delphi survey with 48 respondents using purposive and snowball sampling techniques. partial least squares structural equation modelling (PLS-SEM) was used for analysis of data.

A model was developed to investigate the influence the risk factors inherent in PPP power projects have on each other. Validity of the model was tested based on the data collected. PLS-SEM results indicated the various relationships and interdependencies the risk factors had on each other considering their probability and severity. Both significant and insignificant levels of relationships were found among the various risk factors.

The SEM that was developed to assess the relationships among the risk factors has great value for policy makers in the energy sector, industry practitioners, researchers and industry practitioners. Strategies can be mapped out to mitigate and effectively allocate the risks with the high interdependencies.

Regarding the quantitative impact of the interrelationship among risk factors in PPP power projects, the findings of this research are arguably the first to be presented for the construction sector and contribute to knowledge on PPP practice and further has implications toward achieving power sector risk mitigation.