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This study examines consumers’ usage intention towards retail metaverse banking. This research also investigated the mediating impact of trust and distrust. This research also examined the moderating impact of perceived security concerns.

Firstly, a qualitative study is performed to explore the benefits and sacrifices that may influence usage intention. Further, the quantitative study gathered a total of 308 responses to investigate the proposed hypotheses.

The findings suggest that perceived anthropomorphism and perceived immersion positively impact the usage intention towards retail metaverse banking. Further, lack of social interaction and perceived vulnerability had a negative influence towards retail metaverse banking. Further, trust and distrust were found to be significant mediators. Also, perceived security concern was shown to be a significant moderator.

The study contributes to the metaverse literature and suggests to banks how to enhance usage intention towards retail metaverse banking. The study also enriches the literature on dual-factor theory.

This study aims to investigate the impact of information and communication technology (ICT) investment on the micro, small and medium enterprises (MSME) profitability in the Indian context.

This study used a framework based on the ICT investment and firm size, measuring the impact on profit before depreciation, interest, tax and amortisation of MSME by taking a random sampling of 300 Indian MSME manufacturing firm’s secondary data from the Prowess database. This framework was analysed using the design of experiment (DoE) technique.

The study showed that ICT investment has a significant positive relationship with profitability. This study examines the different ICT investment levels to predict investment strategies and fine-tune profit targets. The critical finding is that ICT investment maximises profit at one million rupees. This discovery aids MSME leaders’ sustainable business decision-making.

This study has an explicit limit to the Indian context, where the firm requirements of countries are different, and these findings need to be validated with many operating variables and applied to more firms with more data. Even so, as a theoretical implication, this study took a novel approach to ICT adoption (through ICT investment) in the Indian MSME sector with guiding levels of ICT investment for each type of firm (i.e. micro, small and medium). This study opens new avenues for investigating researchers and stakeholders by exploring other factors responsible for ICT adoption.

This study uniquely provides practitioners with the functional level of ICT investment for MSMEs in the Indian context. These finding guides top management to make strategic ICT adoption decisions with information symmetry. At the same time, these findings suggest financial institutions astern their credit programme to provide credit for ICT investment in MSMEs.

This study highlights the value of ICT as a practical resource for business owners that significantly makes MSMEs more informed and profitable, thus creating more jobs and incrementing the country’s gross domestic product (GDP).

This study offers unique empirical findings on how decision makers in MSMEs maximise profits through optimal ICT investment levels depending upon the firm size in an emerging economy like India. There is evidence in the study to conclude that ICT is a need of MSME and has implications for firm performance.

The dynamic business environment and intense competition have mandated agility in operations for manufacturing firms. Effective inter-organizational collaboration can make operations more agile. This paper develops an interpretive model to explore the effect of supply chain collaboration (SCC) on supply chain agility (SCA) and, subsequently, on business performance.

A hierarchical model that illustrates the relationship between SCC, SCA and firm performance components is developed using total interpretative structural modeling (TISM). Also, statistical validation of the model has been performed.

The results indicate that the vision and alertness of the firm on the strategic front promote collaboration between supply chain partners. This creates operational agility, helping the firm to absorb fluctuations in demand, thereby enhancing business performance.

The opinion of most respondents was considered to develop the TISM framework over the fuzzy one, which necessitates a significantly more extensive data set. However, multiple discussions with participants can eliminate the prejudice of the majority approach. Also, the paper's development and validation were restricted to Indian manufacturing small and medium-sized enterprises (SMEs). The model can potentially be evaluated in large organizations to provide further insights.

The study blends the factors of SCC and SCA in a novel way to explain their combined impact on business performance. The TISM model addresses the “why” of theory development in addition to the “what” and “how” of it. Using triangulation in combination with the interpretative tool, this study additionally offers methodological value.

This study aims to identify seasonal drought using standardized precipitation index (SPI). The following specific objectives are to generate result and identify seasonal drought and determine different scale of seasonal drought and its impacts on cropping season.

Seasonal SPI was calculated using long-term rainfall data for three seasons. The SPI was calculated using the formula and it is effective for the determinants. This study showed the functional relationship between drought duration, frequency and drought time scale using the SPI. SPI=X−X¯σ.

Seasonal drought occurs more frequently in Bangladesh that affects crops and the agricultural economy every year. More severe drought was recorded during the Kharif-1 and Kharif-2 seasons and most crops were affected in these two seasons. No severe or moderate drought was recorded during the Rabi season. The results showed that monsoon crops were severely affected severely by extreme and severe droughts during the Kharif-2 season. Eventually, the people remain jobless during the monsoon, and they experience food shortages like monga. Several obstacles were recorded during the season, including delayed preparation of land, sowing, transplanting and other farming activities because of monsoon droughts. This study revealed that very frequently, mild dryness occurs in winter, but crop loss is minimal. The scale and occurrence of extreme droughts are more frequent during monsoons and reduce crop yields, affecting livelihoods in the study area. Seasonal drought affects cropping patterns as well as reduce crop yields.

The outcome of this study derived from the secondary data and field data.

This study aims to examine empirically the nature of supply chain disruptions caused by the COVID-19 pandemic, particularly on the Indian automobile sector.

The authors evaluate the stock market performance of individual company and its quantitative relationship to certain variables related to company’s supply chain.

The authors analysed the company’s operations considering several ratios like asset intensity, company size, labour intensity and inventory to revenue.

The results of analysis can help the companies to understand how disruptions in the supply chain can affect the company’s operations and how it is perceived by the investors in the stock market.

Also, investors are benefitted, as they can understand how different companies with different operational characteristics react to global disruptions in supply chains, which in turn would help them to find better investment opportunities.

Although there is some literature available on the qualitative as well as quantitative analysis, the authors go further to analyse the impact of supply chain disruption on the stocks of the automobile sector.

Climate change-related weather events significantly affect rice production. In this paper, we investigate the impact of and interrelationships between agriculture inputs, climate change factors and financial variables on rice production in India from 1970–2021.

This study is based on the time series analysis; the unit root test has been employed to unveil the integration order. Further, the study used various econometric techniques, including vector autoregression estimates (VAR), cointegration test, autoregressive distributed lag (ARDL) model and diagnostic test for ARDL, fully modified least squares (FMOLS), canonical cointegrating regression (CCR), impulse response functions (IRF) and the variance decomposition method (VDM) to validate the long- and short-term impacts of climate change on rice production in India of the scrutinized variables.

The study's findings revealed that the rice area, precipitation and maximum temperature have a significant and positive impact on rice production in the short run. In the long run, rice area (ß = 1.162), pesticide consumption (ß = 0.089) and domestic credit to private sector (ß = 0.068) have a positive and significant impact on rice production. The results show that minimum temperature and direct institutional credit for agriculture have a significant but negative impact on rice production in the short run. Minimum temperature, pesticide consumption, domestic credit to the private sector and direct institutional credit for agriculture have a negative and significant impact on rice production in the long run.

The present study makes valuable and original contributions to the literature by examining the short- and long-term impacts of climate change on rice production in India over 1970–2021. To the best of the authors’ knowledge, The majority of the studies examined the impact of climate change on rice production with the consideration of only “mean temperature” as one of the climatic variables, while in the present study, the authors have considered both minimum as well as maximum temperature. Furthermore, the authors also considered the financial variables in the model.

This study aims to examine the factors that influence the increase in purchase intention toward green batik products with religiosity as an intervening variable.

The study used a survey method that involved a sample size of 185 participants selected through purposive and accidental sampling techniques. The analysis was conducted by using IBM SPSS AMOS 21 software. The collected data were subjected to path analysis using multiple linear regression models.

The result indicated that religiosity plays a mediating role in the association between factors and the intention to purchase green product (GPd) of the Indonesian natural dye batik product. This finding is in accordance with the construction of theory of planned behavior in understanding consumer purchase intentions. GPd, green brand and green price exhibited a positive correlation with green purchase intention (GPI). Interestingly, the price was found to no longer serve as the primary factor in GPI.

The analysis would have been more compelling if it had used a mixed-method approach by introducing the variables of customer satisfaction and promotion.

This research postulates that increased prices are no longer a deterrent to the purchase of GPd. Instead, consumer consciousness regarding GPd plays a pivotal role in driving GPI. GPd have revolutionized individuals’ consumption patterns to contribute to environmental preservation. The use of green batik products is seen as advantageous in helping mitigate environmental degradation.

The present research assesses the impact of religiosity, as an intervening variable, on the augmentation of GPI by gauging its significance in enhancing ecological consciousness and moral values.

This research aims to examine how decision-makers’ demographic traits affect the integration of foreign workforce into Tirolean (Austria) companies. With continuous world migrations, Tirol experiences a great inflow of foreign workforce. While integrating into the workforce, the foreign workers interact with various decision-makers whose demographic traits (e.g., age, gender, nationality) potentially influence the success of the integration process. To gather data on the integration levels of a foreign workforce, the author conducted a questionnaire. Furthermore, several statistical analyses were run to determine if the relationship between demographic characteristics and integration success exists. The study reveals that demographic characteristics influence decision-makers’ acceptance of expatriates, as well as their recruitment, integration, and training and development outcomes. The empirical results indicate the strength of relationships identified through analyses. The study is limited to geographical, as well as the scope of the sample size, as the data are obtained from Tirol only. In addition, the results from the study serve as a basis for future discussions and research.

This study examines the effect of sustainable development goal (SDG) concerns regarding the sustainability issues raised in the United Nations SDG agenda on pro-sustainable travel behavior (PSTB) by building on the norm activation model as well as value theory (altruism), with the latter assumed to moderate the effect of SDG concerns on PSTB.

The model was tested using structural equation modeling (SEM) based on data from 200 USA respondents who have traveled internationally in the past 12 months.

The results confirmed the effect of SDG concerns on positively influencing PSTB both directly and indirectly (through the NAM variables of “responsibility” and “obligation”). Additionally, results revealed that altruism positively moderates the effect of SDG concerns on PSTB.

Results provide tourism businesses and destinations with a better understanding of which aspects of the 17 issues identified in the UN SDG agenda are more likely to influence travelers’ future PSTB and whether such behavioral changes additionally depend on people’s individual altruism levels.

Unlike previous studies focusing mainly on environmental concerns and tourists’ pro-environmental behavior, this study offers a more comprehensive understanding of PSTB in light of today’s UN SDGs.

Given the important role of knowledge resource for firms to pursuit innovation, this paper aims to investigate the influence of knowledge-based human resource management (HRM) practices on innovation performance through the mediating roles of tacit and explicit knowledge sharing (KS). This study also explores the potential moderating role of perceived organizational supports (POSs) in fostering the KS–innovation relationship of firms in the developing and emerging markets.

The relationship among the latent variables is empirically examined through 289 employees from 118 manufacturing and service firms. Confirmatory factor analysis and structural equation modeling were performed to validate the constructs and estimate the regression coefficients of relationships.

The empirical findings of this study support the mediating role of KS behaviors in the relationship between knowledge-based HRM practices and innovation performance. It highlights the important role of POSs in stimulating the influence of KS behaviors on innovation performance.

Future research should investigate the impact of knowledge-based HRM practices on specific forms of innovation via the mediating effects of knowledge management processes to bring better understanding on the importance of knowledge resources in pursuing innovation competence.

The paper significantly contributes to enhancing understanding of the antecedent role of knowledge-based HRM practices in fostering KS behaviors and innovation performance under the moderating effects of POSs. Generally, it advances the body of comprehension of knowledge-based resources and innovation theory.