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3D printing has been warmly welcomed by clothing enterprises for its customization capacity in recent years. However, such clothing enterprises have to face the digital transformation challenges brought by 3D printing. Since the business model is a competitive weapon for modern enterprises, there is a research gap between business model innovation and digital transformation challenges for 3D-printing garment enterprises. The aim of the paper is to innovate a new business model for 3D-printing garment enterprises in digital transformation.

A business model innovation canvas (BMIC), a new method for business model innovation, is used to innovate a new 3D-printing clothing enterprises business model in the context of digital transformation. The business model canvas (BMC) method is adopted to illustrate the new business model. The business model ecosystem is used to design the operating architecture and mechanism of the new business model.

First, 3D-printing clothing enterprises are facing digital transformation, and they urgently need to innovate new business models. Second, mass customization and distributed manufacturing are important ways of solving the business model problems faced by 3D-printing clothing enterprises in the process of digital transformation. Third, BMIC has proven to be an effective tool for business model innovation.

The new mass deep customization-distributed manufacturing (MDC-DM) business model is universal. As such, it can provide an important theoretical reference for other scholars to study similar problems. The digital transformation background is taken into account in the process of business model innovation. Therefore, this is the first hybrid research that has been focused on 3D printing, garment enterprises, digital transformation and business model innovation. On the other hand, business model innovation is a type of exploratory research, which means that the MDC-DM business model’s application effect cannot be immediately observed and requires further verification in the future.

The new business model MDC-DM is not only applicable to 3D-printing garment enterprises but also to some other enterprises that are either using or will use 3D printing to enhance their core competitiveness.

A new business model, MDC-DM, is created through BMIC, which allows 3D-printing garment enterprises to meet the challenges of digital transformation. In addition, the original canvas of the MDC-DM business model is designed using BMC. Moreover, the ecosystem of the MDC-DM business model is constructed, and its operation mechanisms are comprehensively designed.

This study aims to explore a rarely studied form of person–organization fit, perceptual fit, which captures the accuracy of an employee’s understanding of their organization’s culture. The managerial antecedents of perceptual fit were explored to increase understanding about how employees learn their organizational culture and the role that managers play in that process. In addition, the behavioural and attitudinal consequences of perceptual fit were examined to gain a deeper appreciation for the impact of misunderstanding one’s organizational culture on work attitudes and cognitions.

Survey tools were used to measure multiple workplace cognitions, attitudes and values from employees of three small health-care organizations. Organizational culture was measured for each organization so that perceptual fit could be ascertained, which represents an accuracy score of each individual’s comprehension of their organization’s culture. Regression analyses measured the hypothesized associations between perceptual fit and its proposed antecedents and consequences.

The results suggest that leader–member exchange (LMX) and perceived organizational support (POS) are both positively associated with perceptual fit. In terms of the outcomes of perceptual fit, the regression analyses provide support for an association between perceptual fit and psychological empowerment, job satisfaction and organizational commitment.

This study contributes to the literature by exploring how employees come to understand their organization’s culture, and the consequences of differing levels of understanding (i.e. perceptual fit). The study results suggest that managerial action such as LMX and POS can enhance the chances that an employee is able to understand their organization’s culture accurately. Furthermore, this research adds to our understanding of the individual consequences of understanding one’s organizational culture by providing evidence that psychological empowerment is associated with perceptual fit.

This paper aims to assess the impact of digital financial innovation on financial system development in Common Market for eastern and Southern Africa (COMESA). This paper evaluates the dynamic relationship between digital financial innovation measures and financial system development using time series data from COMESA countries for the period 1997–2019.

A dynamic autoregressive distributed lag model (ARDL) was adopted and the mean group (MG), pooled mean group (PMG) and dynamic fixed effect (DFE) of the model were estimated to evaluate the short- and long-run impact. In addition, the dynamic generalized method of moments (DGMM) was adopted for a robustness check. The Hausman test results show PMG to be the most consistent and efficient estimator, while the coefficient of lagged dependent variable of different GMM is less than the fixed effect coefficient, and, as such, suggests system GMM is the most suitable estimator. Data for the study were sourced from World Bank Development Indicator (WDI, 2020), World Governance Indicator (WGI, 2020) and World Bank Global Financial Development Database (GFD, 2020).

The result shows that digital financial innovation significantly impacts financial system development in the long run. As such, the evidence revealed that automated teller machines (ATMs), point of sale (POS), mobile payments (MP) and mobile banking are significant and contribute positively to financial system development in the long run, while mobile money (MM) and Internet banking (INB) are insignificant but exhibit positive and inverse relationship with financial development respectively. Further investigation revealed that institutional quality and a stable macroeconomic environment including their interactive term are significantly imperative in predicting financial system development in the COMESA region.

Researchers recommend a cohesive and conscious policy that would checkmate the divergence in the short run and suggest a common regional innovative financial strategy that could be pursued to incentivize technology transfer needed to promote financial system development in the long run. More so, plausible product and process innovations may be adapted to complement innovative institutions in the different components of the COMESA financial system.

Digital financial innovation services if well managed increase the inherent benefits in financial system development.

To the best of the authors’ knowledge, this paper presents new background information on digital financial innovation that may stimulate the development of the financial system, particularly in the COMESA region. It also exposes the relevance of digital financial innovation, institutional quality and stable macroeconomic environment as well as their interactive effect on COMESA financial system development.

The aim of this study is to examine the nature and determinants of stock market integration between India and other Asia–Pacific countries (Malaysia, Hong Kong, Singapore, South Korea, Japan, China, Indonesia, the Philippines, Thailand and Taiwan) over the period 1991–2021.

Unit root tests, the dynamic conditional correlation-Glosten Jagannathan and Runkle-generalized autoregressive conditional heteroscedasticity (DCC-GJR-GARCH), pooled ordinary least squares (OLS) regression and random effects models are employed for the analysis.

The empirical results show that the DCC between each pair of sample countries is less than 0.5, indicating weak ties between the pairs of sample countries. Also, the DCC between India and other Asia–Pacific stock markets is positive and low, implying low level of integration. The correlation between India and China stock markets is found to be the highest, implying significant level of integration. The main reason for it would be strong economic linkages and bilateral trade relationship between India and China. Moreover, gross domestic product (GDP), interest rate (IR), consumer price index (CPI)-inflation and money supply (MS) differentials are the major driver of stock market integration between India and other Asia–Pacific countries.

The findings of the study have important implications for investors, portfolio managers and policymakers. It is found that the DCC between India and other Asia–Pacific countries (considered in the study) except China is low, which indicates weak ties between the pairs of sample countries. This implies that the Indian stock market provides good investment opportunities for foreign investors. Also, investors and portfolio managers can attain more diversified benefits and can minimize country risk by investing across Asia–Pacific countries. Further, knowledge about the factors that integrate the Indian stock market with the other Asia–Pacific stock markets will help policymakers frame suitable economic and financial stabilization policies.

This study contributes to the extant literature: first, by examining the linkages of Indian stock market with other Asia–Pacific countries; second, although previous studies confirmed the existence of linkages among the various stock markets, few researchers pay attention to the factors driving the process of stock market integration. This study provides additional evidence by examining the significant macroeconomic factors driving the process of such integration in the Asia–Pacific region considered under the study.

It is known that a conflict exists between consumers’ materialistic and green values. Previous research has focused on values conflict consequences. Antecedents of consumers’ materialistic and green values conflict remain understudied. This study aims to explore the antecedents of consumers’ materialistic and green values conflict.

An exploratory type research design was applied. Overall 22 interviews were conducted with consumers that had materialistic and green values conflict. The transcripts of the interviews were analyzed using content analysis with Maxqda software.

The findings demonstrate consumers' negative attitudes towards consumption, understood as consumerism. Results indicate that value conflict is related to unpleasant emotions such as guilt, anxiety, helplessness and remorse. Guilt is the most prominent emotion associated with the conflict of values. The study identifies dissonant information, environmental knowledge, social norms, impulsive buying and mindfulness as antecedents of materialistic and green values conflict.

The novelty of the study is the antecedents of the materialistic and green values conflict. This study makes a valuable contribution to the academic discourse on sustainable consumption, consumer materialism and green values by providing a deeper understanding of the values conflict experienced by consumers who hold materialistic and green values. The main significance of this study is that it provides valuable insights from qualitative research into the antecedents of the conflict between consumers' materialistic and green values.

This paper aims to examine the relationship between environmental, social and governance (ESG) performance and systemic risk sensitivity of Chinese listed companies. From the consumer loyalty and investor structure perspectives, the relationship between ESG performance and systemic risk sensitivity is analyzed.

Since Morgan Stanley Capital International (MSCI) ESG officially began to analyze and track China A-shares from 2018, 275 listed companies in the SynTao Green ESG testing list for 2015–2021 are selected as the initial model. To measure the systematic risk sensitivity, this study uses the beta coefficient, from capital asset pricing model (CPAM), employing statistics and data (STATA) software.

The study reveals that high ESG rating companies have high corresponding consumer loyalty and healthy trading structure of institutional investors, thereby the systemic risk sensitivity is lower. This paper reveals that companies with high ESG rating are significantly less sensitive to systemic risk than those with low ESG rating. At the same time, ESG has a weaker impact on the systemic risk of high-cap companies than low-cap companies.

The study helps the companies understand the influence of market value on the relationship between ESG performance and systemic risk sensitivity. Moreover, this paper explains explicitly why ESG performance insulates a firm’s stock from market downturns with the lens of consumer loyalty theory and investor structure theory.

The paper provides new insights on the company’s ESG performance that significantly affects the company’s systemic risk sensitivity.

People donate to charities with the aim of improving society. Yet, many charities fail to use donations efficiently or have ineffective interventions. The authors explore the strategic operational priorities and processes that enable charities to efficiently implement their interventions and have a positive impact on society.

The authors first review the literature on charities to gain a deeper understanding of the current state of knowledge on charity operations. The authors then employ the lens of paradox theory and perform a qualitative investigation of six case studies to explore various aspects of the operations of charities that are known for being cost-effective.

The authors reveal how the strategic operational decisions of charities, as well as the processes they implement, help them resolve the tensions arising from the cost-effectiveness paradox. The authors show that cost-effective charities make strategic operational decisions that help maintain two diverging priorities: prioritizing the status quo and prioritizing change in how they deliver value. Another set of strategic decisions helps balance these two diverging priorities. The authors then show how these charities create and then maintain cost-effective operations.

The authors address recent calls for research on non-profit organizations in the field of operations management. To authors’ knowledge, it is the first in-depth study of exemplary charity operations. The results can be used by charity executives as a benchmarking tool when they develop and implement their charitable interventions and by government agencies and potential donors when they select charities for their donations. Finally, the results should have implications for other organizations trying to have a positive societal impact.

There is extensive literature on the effect of military expenditure on economic growth. However, there is also a wide gap in the literature on the relationship between productivity and innovation, which is considered the driving force of economic growth and military expenditures. To this end, this study examines the effect of military expenditures on economic growth, innovation and labor productivity for the period 1995–2019 in most militarized countries.

The tests used in the study's empirical analysis are techniques that take into account cross-sectional dependence and heterogeneity. The stationarity of the variables was tested with the Pesaran’s (2007) unit root test. Then, empirical findings were revealed based on the analysis through Westerlund’s (2008) cointegration test and Emirmahmutoglu and Kose’s (2011) panel causality test.

According to the empirical results, there is a long-run relationship, in other words, a cointegration between military expenditures and productivity, innovation and economic growth. Additionally, there are causality relationships between military expenditures and productivity, innovation and economic growth.

These results support the arguments of military Keynesianism and the Benoit hypothesis.

Despite the widespread theoretical debate, no empirical study tests the effect of military expenditure on productivity and innovation to the author's best knowledge. Hence, this study aims to fill this gap in the literature. Moreover, the fact that the econometric method used is based on second generation tests and the timeliness of the period range makes the study's findings more significant.

The purpose of this research is to propose and empirically validate a theoretical framework to investigate the willingness of the elderly to disclose personal health information (PHI) to improve the operational efficiency of AI-integrated caregiver robots.

Drawing upon Privacy Calculus Theory (PCT) and the Technology Acceptance Model (TAM), 274 usable responses were collected through an online survey.

Empirical results reveal that trust, privacy concerns, and social isolation have a direct impact on the willingness to disclose PHI. Perceived ease of use (PEOU), perceived usefulness (PU), social isolation, and recognized benefits significantly influence user trust. Conversely, elderly individuals with pronounced privacy concerns are less inclined to disclose PHI when using AI-enabled caregiver robots.

Given the pressing need for AI-enabled caregiver robots due to the aging population and a decrease in professional human caregivers, understanding factors that influence the elderly's disclosure of PHI can guide design considerations and policymaking.

Considering the increased demand for accurate and comprehensive elder services, this is the first time that information disclosure and AI-enabled caregiver robot technologies have been combined in the field of healthcare management. This study bridges the gap between the necessity for technological improvement in caregiver robots and the importance of transparent operational information by disclosing the elderly's willingness to share PHI.