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The purpose of the study was to examine the effect of corporate social responsibility (CSR) and marketing capability on consumer behavioral responses in the mobile telecommunication industry in Ghana. Particularly, the study estimated the moderating effect of marketing capability on the relationship between CSR and consumer behavioral responses.

Both customers and employees of three major mobile telecommunication companies were sampled for this work. A mixed linear regression technique was used to examine the relationship between corporate responsibility, marketing capability and customer behavioral responses.

The empirical results revealed that marketing capabilities moderate the relationship between CSR and consumer responses in the telecommunication industry.

The study proposes practical dimensions to the mobile telecommunication companies that the extensive development of strong marketing capabilities serves a conduit for CSR to achieve favorable consumer responses.

The results have opened up rather a limitation studies on the moderation role marketing capabilities in relationship between CSR and consumer behavioral responses in the telecommunication industry.

There is a pressing need to increase investments in sustainable infrastructure to promote low carbon economic growth and ensure environmental sustainability. Consequently, this study examines the socio-political factors underlying the adoption of green bond financing of infrastructure projects.

Primary data was gathered from experts with advanced experience in, or knowledge of green bonds in the Kumasi Metropolis. To identify respondents with pertinent knowledge that is relevant to the study, purposive and snowball sampling techniques were used. One-sample t-test and relative importance index were used in this study's statistical analysis.

‘Training and experience with sustainable finance’ was seen as the most important social factor underlying the adoption of green bond financing of infrastructure projects by the respondents and ‘Governmental tax-based incentives’ was rated as the leading political factor.

This pioneering research attempts to ascertain the socio-political factors affecting the adoption of green bond financing of infrastructure projects. Emergent results of analysis and concomitant discussions add knowledge to fill a void in literature on the social and political factors affecting the adoption of green bond financing of infrastructure projects in developing countries.

The study aims to determine the long and short-term causal relationships between the variables associated with the adjustment of monetary policy and the stock market in India in the presence of structural breaks.

The study employed the autoregressive distributed lag (ARDL) bounds test and the Error Correction Model to assess long- and short-term causal relationships. The study also used non-frequentist Bayesian inferences for the validity of estimation robustness. The Bai–Perron test is used to identify breakpoint dates for the Indian stock market index, and the Granger Causality test is employed to ascertain the direction of causality.

The F-bounds test reveals cointegration among the variables throughout the examined period. Specifically, the weighted average call money rate (WACR), inflation (WPI), currency exchange rate (EXE), and broad money supply (M3) exhibit statistical significance with precise signs. Furthermore, the study identifies the negative impact of the COVID-19 outbreak in March 2020 on the Indian stock market.

Although the study provides significant insights, it is not exempt from constraints. A significant limitation is selecting a relatively limited time period, specifically from April 2008 to September 2023. The limited time frame of this study may restrict the applicability of the results to more comprehensive economic settings, as dynamics between the monetary policy and the stock market can be influenced by multiple factors over varying time periods. Furthermore, the utilisation of the Weighted Average Call Money Rate (WACR) rather than policy rates such as the Repo rate presents an additional constraint as it may not comprehensively account for the impacts of particular policy initiatives, thereby disregarding essential complexities in the connection between monetary policy variables and financial markets.

The findings of the study suggest that investors and portfolio managers should consider economic issues while developing long-term investing plans. Reserve Bank of India should exercise prudence to prevent any discretionary measures that may lead to a rise in interest rates since this adversely affects the stock market. To mitigate risk, investors should closely monitor the adjustment of monetary policy variables.

The study has important social implications, especially regarding the lower levels of financial literacy among investors in India. Considering the complex nature of the study’s emphasis on monetary policy adjustments and their impact on the stock market. Investors face the risk of significant losses due to unexpected adjustments in monetary policy. Many individuals may need help understanding how policy changes impact their investments. Therefore, RBI must consider both price and financial stability when formulating monetary policies. Furthermore, market participants should consider the potential impact of fluctuating monetary policy variables when devising their long-term investment strategies. Given that adjustments in interest rates can markedly affect stock market dynamics, investors must carefully assess the implications of monetary policy decisions on their portfolios.

The study uses dummy variables in the ARDL model to represent structural breaks that emerged from the COVID-19 pandemic (as determined by the Bai–Perron multiple breakpoint test). The study also used the Perron unit root test to find out the stationary of the series in the presence of structural breaks. Additionally, the study also employed Bayesian inferences to affirm the robustness of the estimates.

This study aims to explore the differences in the tourists’ perceived destination image on travel e-commerce platforms (e.g. Ctrip and Fliggy) and social media platforms (e.g. Xiaohongshu and Weibo).

The purpose of this paper is to assess the impacts on production of five fruit crops from 1961 to 2018 of energy use, CO₂ emissions, farming areas and the labor force in China.

This analysis applied the autoregressive distributed lag-bound testing (ARDL) approach, Granger causality method and Johansen co-integration test to predict long-term co-integration and relation between variables. Four machine learning methods are used for prediction of the accuracy of climate effect on fruit production.

The Johansen test findings have shown that the fruit crop growth, energy use, CO₂ emissions, harvested land and labor force have a long-term co-integration relation. The outcome of the long-term use of CO₂ emission and rural population has a negative influence on fruit crops. The energy consumption, harvested area, total fruit yield and agriculture labor force have a positive influence on six fruit crops. The long-run relationships reveal that a 1% increase in rural population and CO₂ will decrease fruit crop production by −0.59 and −1.97. The energy consumption, fruit harvested area, total fruit yield and agriculture labor force will increase fruit crop production by 0.17%, 1.52%, 1.80% and 4.33%, respectively. Furthermore, uni-directional causality is correlated with the growth of fruit crops and energy consumption. Also, the results indicate that the bi-directional causality impact varies from CO₂ emissions to agricultural areas to fruit crops.

This study also fills the literature gap in implementing ARDL for agricultural fruits of China, used machine learning methods to examine the impact of climate change and to explore this important issue.

The purpose of this paper is to deliver a structured literature review of existing literature on agri-fresh food supply chain quality (AFSCQ) over a period of 23 years (1994 to mid-2016) and provide a platform for practitioners and researchers trying to identify the existing state of work, gaps in current research, and future directions in the field of AFSCQ.

The existing literature is classified on the basis of several classes like number of publications per year, journal-wise publications, studies across various countries, growth of empirical research, data analysis methods or tool used, issues related to supply chain quality as well as performance measurement (with respect to entity of analysis, level of analysis and element of exchange).

Most of the research publications discuss issues in developed countries, while relatively lesser publications are available on issues in developing countries. Hence, larger opportunities in the field of AFSCQ are available in developing countries. Empirical research is also growing in the field of AFSCQ. Largely research publications make use of “case study” research approach and “statistical analysis” as a quantitative tool of research. The literature is also categorized under the various issues of supply chain quality such as sustainability management, information management, logistic management, collaboration and coordination management, strategic management, demand management, inventory management, food safety, performance management, supply chain integration, supplier management, quality management, etc. It was found that in the majority of articles, information management, sustainability management, and logistics management are very critical issues as far as AFSCQ is concerned. Performance measurement of agri-fresh food supply chain is also on a growing stage. It is also an integral part of AFSCQ.

Most of the prior reviews are concentrated on a particular issue as production and distribution planning for agri-foods, temperature monitoring, corporate and consumer social responsibility, traceability system and ignore the wider perception. There exists a necessity of having a detailed review to cover up all the issues in AFSCQ. This review fills this gap in the extant AFSCQ literature.

Our study focuses on providing empirical evidence regarding the optimization of podcasting in asynchronous learning. This action research aimed to innovate the delivery of asynchronous classes using differentiated podcasts.

We utilized action research as the research design for the study. Participating in action research entails developing practical knowledge to improve educational practices through specific methods and critical perspectives (Sáez Bondía and Cortés Gracia, 2022). According to Burns (2007), action research involves deliberate interventions usually prompted by identified issues, mysteries or inquiries that individuals in the social setting seek to improve or change. Implementing changes to enhance individuals' actions and understanding within their context is the focus of action research (Kemmis, 2010). The study’s approach is ideal for examining new practices and gaining enhanced theoretical insights (Altrichter et al., 2002). Engaging in action research helps enhance understanding and empowers us to impact and enhance practices through continuous reflection, exploration and action. Through this iterative process, we can continuously enhance our comprehension and make substantial strides toward fostering positive transformation.

The study findings showed an apparent rise in student regulation and engagement and remarkable enhancements in learning outcomes, as demonstrated by differences in pre-test and final exam scores. These results highlight the actual effect of specialized podcasts on self-paced inducing students' self-efficacy in learning. Our research provides valuable insights on effectively incorporating podcasts into education, offering innovations and improvement of practice among educators and institutions adapting to the ever-changing landscape of the educational environment while catering to the diverse needs of the learners. This research is pioneering research catering to the various learning styles of asynchronous learning environments.

Although our current sample offered valuable insights, upcoming studies could gain from more extensive and more diverse participant groups to strengthen the reliability of our results and guarantee broader applicability across various demographics and contexts. Moreover, the length of our intervention may have been relatively brief, which could have limited our ability to evaluate the long-term impact of customized podcasts on learning results. Continued investigation into the long-term effects of these interventions could provide valuable insights into their effectiveness over time and help shape the creation of more lasting educational approaches.

Innovation in asynchronous learning differentiated teaching attuned to the diverse learning styles of the students.

The study promotes equitable education, which eventually promotes learning outcomes of the students.

We created differentiated podcasts tailored to the learning styles of the students. This research is pioneering research catering to the various learning styles of asynchronous learning environments.

With theoretical underpinnings in the conservation of resources theory, this research aims at understanding the link between workplace ostracism (WPO) and its effects on customers' interests in the context of COVID-19, with the mediation of stress and moderation of self-efficacy (SE).

The study followed a time-lagged design. A sample of 217 frontline employees working in the food sector of southern Punjab, Pakistan, responded to the study questions using the survey method with structured questionnaires. A Statistical Package for the Social Sciences (SPSS) tool was utilized for data analysis with bootstrapping and PROCESS macro.

The findings show that an important mechanism by which ostracism translates into customer service sabotage (CSS) is the increase in perceived stress levels of the employees. Additionally, SE was found to be an important personal resource that acts as a moderator in the said relationship.

Employees with high SE sense less workplace stress even during a pandemic. Leadership should consider the stress-alleviating effect of SE for lessening the damaging influence of WPO on customers.

The study fills an important empirical gap in the context of the COVID-19 pandemic, by showing that due to resource loss perceived by employees while being targeted by ostracism, they may decide to transfer their frustration towards organizational customers by sabotaging their service experience.

The purpose of this study is to explore the potential and growth of big data across several industries between 2016 and 2020. This study aims to analyze the behavior of interest in big data within the community and to identify areas with the greatest potential for future big data adoption.

This research uses Google Trends to characterize the community’s interest in big data. Community interest is measured on a scale of 0–100 from weekly observations over the past five years. A total of 16 industries were considered to explore the relative interest in big data for each industry.

The findings revealed that big data has been of high interest to the community over the past five years, particularly in the manufacturing, computers and electronics industries. However, over the 2020s the interest in the theme decreased by more than 15%, especially in the areas where big data typically had the greatest potential interest. In contrast, areas with less potential interest in big data such as real estate, sport and travel have registered an average growth of less than 10%.

To the best of the author’s knowledge, this study is original in complementing the traditional survey approaches launched among the business communities to discover the potential of big data in specific industries. The knowledge of big data growth potential is relevant for players in the field to identify saturation and emerging opportunities for big data adoption.

The authors investigate the varying impact of three categories of conflicting consumer reviews (i.e. conflicting opinions on attributes of a product item, conflicting ratings of an item and the intensity of conflicting reviews of an item) on the potential customers' perceived informativeness, which is expected to affect the perceived correct purchase.

To test their proposed hypotheses, the authors conducted an experiment using a 2 × 2 × 2 factorial design for each conflict type comprising two levels (low vs high).

The results of this study found that conflicting opinions on product attributes can enhance potential customers' perceptions of informativeness and subsequent correct purchase decisions while conflicting ratings and the intensity of conflicting reviews can diminish potential customers' perceptions of informativeness. In addition, conflicting ratings negatively moderate the effect of conflicting attributes on perceived informativeness such that the positive effect of conflicting attributes on perceived informativeness will be less prominent when conflicting ratings are present (vs absent).

While potential customers are browsing product descriptions, reviews and comments from other purchasers are also playing a role in influencing a potential customer's purchase decision. However, given the different experiences and temperaments of individuals, the subjective remarks and ratings of individuals are sometimes inconsistent or even conflicting, which can lead to confusion among potential customers. The authors categorize the positive or negative effects of the three conflicting reviews based on the two dimensions of ease of capture and product diagnosticity. The findings can help platforms optimize the display of product reviews to help potential customers make more accurate purchase decisions.