Purpose This study examines how technology-focused firms convert strategic technology orientation into business effectiveness by developing customer-centric analytics as a firm capability that is embedded in customer-facing routines. Design/methodology/approach Survey data from 203 senior managers in technology-oriented firms were analyzed using structural equation modeling. Instrument development followed a multi-stage process including expert interviews and pilot testing. Findings Technology-focused strategy is positively associated with customer-centric analytics, which is in turn positively associated with business effectiveness. The indirect effect through customer-centric analytics is significant, while the direct effect is not, a pattern consistent with full mediation. Customer-centric analytics therefore operationalizes a technology-focused strategy into business outcomes. Research limitations/implications Cross-sectional design and IT-services-dominant sample constrain causal inference and generalizability. Future longitudinal and multi-industry studies are encouraged. Practical implications Technology investments deliver stronger returns when customer analytics is embedded in day-to-day routines, such as diagnosing where customer-facing work breaks down and guiding ongoing improvement. Tool acquisition alone rarely produces performance gains. Originality/value The study conceptualizes customer-centric analytics as a firm capability embedded in customer-facing routines and offers evidence consistent with full mediation, advancing work that has treated analytics as a firm-level resource rather than as a set of practices inside daily work.
Purpose This study examines how green finance helps to achieve responsible consumption and production (RCP) through minimizing material pressure on the economy. The study primarily focuses on the role of institutional and macroeconomic factors to make green finance work better for responsible production and consumption. Design/methodology/approach The paper uses a Panel Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL) model to represent both long-run and short-run relationships. The study uses data of selected nations from the Asia–Pacific region from 2010 to 2024. A novel RCP pressure index is created by principal component analysis using Domestic Material Consumption and Material Footprint. The key explanatory variables are government effectiveness and regulatory quality for institutional conditions; Gross domestic product per capita (GDP) and research and development (R&D) expenditure for macroeconomic controls. Findings The results of the study indicate that strong government control and regulations enhance the transmission of green finance to sustainable results as institutional factors. Results indicate that 1% growth in green bonds reduces the responsible consumption and production pressure (RCPP) index by 0.164 percent implying that green financial growth has been converted into real eco-friendly consumption and production practices. Although material pressure grows in the short run due to economic growth but R&D investment reduces material intensity in the long-run. Originality/value To the best of the author's knowledge, the study is one of the few empirical ones that develops an RCP pressure index. The research presents empirical evidence on how green finance, institutional quality and macroeconomic conditions interact to influence the resultant responsible production and consumption.
Purpose This study aims to examine the structural limitations of post-convergence global accounting systems and to develop a conceptual framework that enhances the adaptability of International Financial Reporting Standards (IFRS). While IFRS has improved global comparability, challenges remain in enforcement consistency, SME inclusiveness, digital integration, and sustainability reporting. The study introduces the Global Accounting Standards Extension Framework (GASF) as an evolutionary, extension-based approach designed to address these gaps. By proposing a tiered, modular and digitally enabled structure, the research seeks to contribute to the ongoing debate on the future direction of global accounting standard-setting. Design/methodology/approach The study adopts a qualitative and exploratory research design consistent with its theory-building objective. A structured comparative analytical framework is employed to examine differences among U.S. GAAP, IFRS and the proposed GASF across key dimensions such as scalability, digital compatibility and implementation flexibility. The analysis is based on secondary sources, including academic literature, standard-setting documents and institutional reports. To bridge theory and practice, the study incorporates a single illustrative case from an emerging economy context. The approach emphasizes conceptual clarity and analytical depth rather than empirical generalization. Findings The findings suggest that existing global accounting frameworks face limitations in addressing diverse institutional conditions, SME reporting needs and digital transformation requirements. The proposed GASF demonstrates enhanced adaptability through its tiered and modular design, enabling proportional reporting while maintaining IFRS-based recognition and measurement. The framework also shows stronger alignment with digital reporting environments and sustainability disclosure requirements, including IFRS S1 and S2. The case illustration indicates potential improvements in reporting consistency, efficiency and system integration, although implementation outcomes remain dependent on institutional and technological readiness. Originality/value This study contributes to the literature by reframing accounting convergence as an evolutionary process and by introducing an extension-based approach to global standard-setting. Unlike existing GAS frameworks, GASF integrates scalability, digital adaptability and sustainability alignment within a single coherent structure while preserving IFRS legitimacy. The study offers practical value for regulators, practitioners and policymakers by providing a flexible and inclusive reporting model. It also establishes a foundation for future empirical research on adaptive accounting frameworks in diverse institutional and technological environments.
Purpose During the peak of the COVID-19 pandemic, the airline industry went through turbulent times due to worldwide travel restrictions. Many airlines struggled to keep their heads above water. However, the post-pandemic reorder and restructuring across the industry present a glimmer of hope for a dramatic rebound for some surviving airlines. This article is intended to aid airline managers in formulating innovative business strategies that can better align with potential changes in airline passengers' travel behaviors and service requests in the post-pandemic world.Design/methodology/approach To identify service attributes crucial for luring prospective passengers within the Kano model framework, we collected empirical data from past and prospective passengers in the United States. Then, we conducted a series of multivariate analyses to test whether there are significant differences in the service quality attributes of pandemic and post-pandemic airline passengers.Findings After experiencing the COVID-19 pandemic, airline passengers' perceived importance of certain service attributes, such as cheap airfare, on-time arrival/departure and airplane cleanliness, changed. On the other hand, regardless of the COVID-19 pandemic, airline passengers consistently prioritized air safety and proper baggage handling when evaluating airline service quality and choosing an airline.Originality/value This article is one of the first attempts to compare pandemic and post-pandemic airline passengers' behavioral patterns based on multi-period studies. In addition, unlike most extant airline studies, this article proposes a Kano model to capture dynamically changing passenger priorities and help the airline industry adjust its service improvement and passenger retention strategies.
Purpose The current research seeks to determine the influential attributes of influencers and examine the influence of food influencers (food bloggers) on consumers' purchase intention.Design/methodology/approach Firstly, the content analysis method was applied to identify the characteristics of the influencers, and after extracting factors and characteristics from previous studies, the factors were categorized based on similarities and experts' opinions. Then, an integrated model was designed based on the research hypotheses. In the second step, an online survey was performed on 291 Instagram users.Findings The results of structural equation analysis demonstrated that the influence of three factors: persuasive power, the scope of influence and influencer honesty, is stronger on purchase intention compared to other characteristics. The findings of this paper presented comprehensive recommendations on the paths to success for brands, marketing experts and influencers and provided valuable insights for influencers, food business owners, restaurant managers and audiences to build persuasive influencer marketing strategies and these lead to the consumers' encouragement to buy more.Originality/value The theoretical contribution of this study extends the food influencer literature and by identifying the most frequent and effective features of food industry influencers (key elements of food bloggers persuasion) on the purchase intention of followers on Instagram, it provides insights into how food industry professionals can use social media influencers to develop effective marketing strategies and enhance strong relationships.
PurposeAs manufacturing organizations have been increasingly adopting digital technologies to manage quality, understanding the strategic role of Quality 4.0 (Q4.0) in achieving other organizational outcomes such as sustainability, becomes essential. This study examines the associations of Q4.0 and data-driven culture (DDC) with sustainable performance (SP), and the mediating roles of green organizational orientation (GOO) and Q4.0 in the relationship between DDC and SP among manufacturing organizations.Design/methodology/approachThis empirical study employed the Partial Least Squares Structural Equation Modeling technique for assessing the model using data collected from 121 manufacturing organizations in Pakistan.FindingsThe findings show that Q4.0 is positively associated with GOO and SP. Meanwhile, a strong DDC is positively associated with the implementation of Q4.0, environmentally responsible manufacturing practices and stronger SP. The results also indicate that Q4.0 and GOO mediate the relationship between DDC and SP.Research limitations/implicationsThe study's findings emphasize the importance of adopting a digital approach to quality and fostering a culture that promotes data use for achieving environmentally and socially responsible outcomes.Practical implicationsThe study offers significant insight for executives, managers and policymakers in navigating the challenges of embedding sustainability into manufacturing operations within developing economies. The significant indirect effect of DDC through GOO and the serial mediation through Q4.0 and GOO suggests that investments in digital technologies alone are insufficient to achieve sustainability outcomes unless they are embedded within complementary organizational processes and values.Social implicationsThis work provides insight into the demanding issue of sustainability, emphasizing how Q4.0 adoption involves optimizing processes and enhancing the quality of products and services to promote sustainability. The study offers significant insight for executives, managers and policymakers in navigating the challenges of embedding sustainability into manufacturing operations within developing economies. By demonstrating how Quality4.0 and DDC contribute to SP, the research provides a roadmap for aligning digital transformation efforts with environmental and operational objectives.Originality/valueUnlike previous studies on Q4.0, which have tended to theorize or test the direct impact of Q4.0 on SP, the current study proposes and tests a more comprehensive model by considering the combined effect of Q4.0 and data-favoring culture as well as the paths through which their joint impact leads to SP.
Purpose-This article examines the possible impact of blockchains on over-the-counter (OTC) derivatives markets. The article highlights the advantages as well as the risks and challenges of this technology, thereby contributing to the literature on blockchain adoption. Design/methodology/approach-This article reviews existing innovation and financial literature, followed by a conceptual, theoretical part where the impact of the distributed ledger technology on OTC derivative markets is explained. Findings-Blockchain technology and smart contracts enable process innovation for OTC derivatives markets, given that they could lead to enhanced automation and fewer manual errors. Yet, some barriers have to be overcome for DLT to be widely adopted. Research limitations/implications-Because there has not been empirical data available regarding the usage of this technology, no empirical analyses could have been performed. Practical implications-The paper provides a phased implementation framework for DLT adoption in OTC derivatives markets and identifies critical success factors at each stage of adoption. Originality/value-This article makes a significant contribution to the literature by explaining the ways in which blockchain technology facilitates process innovation. Furthermore, it enhances the body of research on disruptive technologies and offers valuable insights into how regulatory frameworks can foster innovation.
Purpose Korean multinational firms have sought to leverage the Korean Wave as a unique selling point in the global retail market. To clarify the validity of such attempts, this paper aims to examine whether Korean waves influence the online retail purchase behavior of affected foreign consumers. Design/methodology/approach This paper develops a series of hypotheses and tests them using structural equation modeling and confirmatory factor analysis of the empirical data. Findings The descriptive data analysis and hypothesis test results revealed that national branding through the Korean Wave enhanced the favorable impression of Korean products, making Korean e-tailers more competitive in the global retail marketplace. Originality/value This paper is one of the first of its kind to assess the extent to which popular culture influences online retail purchase behaviors and verify the theory of planned behavior using empirical analysis of survey data obtained from Vietnamese consumers.
PurposeThis study examines factors that influence professionals' tenure during their initial public accounting careers. Design/methodology/approachUsing survey data, the study employs ordered logistic regression analyses that include mentoring experiences, performance, gender, educational attainment, and firm size as explanatory variables, and tenure length as the dependent variable. FindingsHigh performance (having a CPA credential) and having a mentor in the first three years of employment are positively associated with longer tenure in initial public accounting careers. While career development function of mentoring – specifically, having a mentor who opens the door to challenging assignments – benefits both genders, technical assistance from a mentor significantly improves tenure for women only. Women who participate in a combination of both formal and informal mentoring are more likely to have longer tenure. Conversely, firm size and advanced educational attainment are negatively associated with tenure. No statistically significant gender differences were observed in overall tenure length. Originality/valueThe study empirically highlights the importance of different functions and types (formal, informal, or both) of mentoring, performance, and gender in shaping initial tenure in public accounting.
PurposeThis study aims to examine the antecedents of retail investors' satisfaction and behavioural intention to use AI-enabled stock trading apps in India.Design/methodology/approachAn online survey was conducted using a structured questionnaire administrated through Google Forms, collecting data from 314 investors who regularly use AI-driven stock trading apps in their investment decisions. Confirmatory Factor Analysis (CFA) was used to assess the constructs' validity and reliability, and, Structural Equation Modelling (SEM) was employed to test proposed hypothesised relationships in the conceptual framework.FindingsThe results of the study reveal that performance expectancy (PE), social influence (SI), facilitating conditions (FC), self-efficacy (SEF) and personal innovativeness (PI) positively influence retail investor satisfaction (SAT) with AI-enabled stock trading apps, whereas effort expectancy (EE) and information quality (IQ) have significant adverse effects on satisfaction. Furthermore, Information Quality and self-efficacy have a significant positive effect on behavioural intention (BI). In addition, satisfaction is found to have a significant effect on investors' intention to use stock trading apps.Practical implicationsThe findings suggest that, AI-based stock trading developers may prioritise intuitive application design, high-quality information delivery and user-focused interactions to boost potential investors' adoption. Additionally, regulatory and policymakers may use results to promote sustained usage of AI-based trading apps.Originality/valueThis study strengthens the literature on AI-based stock trading by examining the retail investors' behaviour in an emerging market context, specifically India, where limited empirical studies explored this contemporary research area. The study employed Unified Theory of Acceptance and Use of Technology (UTAUT) by incorporating three additional constructs, such as self-efficacy, information quality and personal innovativeness, to better explore adoption behaviour, which was less explored in earlier literature from the retail investors' perspective.
PurposeThe purpose of this study is to investigate the effect of incentive strategy on employee performance: moderating mediating effect of organizational commitment and job satisfaction in the hospitality industry in Nigeria. Design/methodology/approachThis study used a quantitative approach to gather data, giving questionnaires to 335 full-time workers of three- and four-star hotels in Northeast Nigeria. The study hypotheses were empirically tested using the bootstrapping technique and the structural equation modeling approach. FindingsThe results confirm the positive and significant effects of incentive strategies (intrinsic and extrinsic), employee job satisfaction, and organizational commitment on employee performance. The positive significant effect of motivational strategies on employee job satisfaction was documented. A partial mediating effect of job satisfaction was documented. However, job satisfaction has no mediating impact, while the moderating effect of organizational commitment was documented. Practical implicationsBased on this study, practitioners should provide in-accordance incentives and rewards to hardworking employees in order to provide them with excellent working environments and suitable employment conditions, increase employee loyalty, reduce attrition, and draw in promising talent. Originality/valueIn contrast to earlier research, this study contribution concentrates on the moderating effect of organizational commitment and the mediating effect of employee work satisfaction in the hospitality industry. It draws attention to the industry's ongoing difficulties in luring and keeping workers.
PurposeThis study examines the long-term effects of organic social media marketing (OSM) on both online and brick-and-mortar (B&M) casinos.Design/methodology/approachWe propose a two-step framework in which casinos rely on organic content on social media to foster user engagement and trust, followed by transaction-based promotions to deepen customer relationships. Using data from Atlantic City casinos, OSM is modeled as a latent construct, and its effects are analyzed through a three-stage structural equation model.FindingsThe findings show that OSM generates sustained positive impacts on revenues for both online and B&M casinos while amplifying the effectiveness of traditional promotional expenditures for B&M casinos.Research limitations/implicationsOur study does not directly measure consumer conversion from organic or paid advertising in the casino industry. The reliance on platform-level rather than casino-specific social media metrics introduces potential endogeneity concerns as observed correlations between social media user shares and casino revenue growth may be spurious. Additionally, our proxy for OSM effectiveness, the residuals derived from the online revenue regression model, has limitations because it does not fully account for other influential factors such as posting frequency, sentiment, and interactive engagement that may also shape online casino performance.Practical implicationsThe study shows that effective OSM engagement is reinforced through organic interest communities, cross-platform interactions, and third-party websites rather than through social media platforms alone. For B&M casinos, integrating OSM with traditional promotions amplifies revenue outcomes. In contrast, online casinos may experience diminishing returns when aggressive promotions undermine the authenticity of organic messaging.Social implicationsOur research indicates that the two-step OSM campaigns can originate from professional or employment-oriented social media platforms such as LinkedIn and often begin with sports- or entertainment-related E-news before transitioning to gambling content. This blurring of informational and promotional boundary highlights the ethical dilemma of balancing freedom of expression on social media with the need to protect consumers from manipulative and potentially harmful marketing practices-an issue with significant economic and political implications.Originality/valueThis study demonstrates that a two-step OSM strategy can enhance revenue performance for both online and B&M casinos by addressing the inherent limitations of direct social media marketing. Extending beyond the casino industry, our research contributes to the literature on OSM and omnichannel strategy by developing a theoretical and empirical model that explicates both the direct and indirect mechanisms through which OSM operates in a cross-channel context.
Purpose This research investigates the mediating role of social media (SM) engagement in the relationship of content types with purchase motivation, that is differentiation-oriented, informative and interactive content. Further, it intends to study the moderating impact of firms' digital capabilities, that is use of SM and online marketing capabilities, on the relationship of SM engagement with purchase motivation. Design/methodology/approach The research employs a positivist philosophy, a deductive approach and a survey research strategy. Respondents were selected randomly from followers of the SM pages of micro firms in Pakistan. Micro firms operating only in grocery, food items, apparel and supplies were considered for data collection. Reliability and validity analysis were conducted as part of the measurement model, followed by mediation and moderation analysis using structural equation modeling. Findings The statistical analysis confirmed that all three content types, differentiation-oriented, informative and interactive, have a positive relationship with purchase motivation and SM engagement mediates the above-mentioned relationships. Results further validated that entrepreneurial/firm capabilities, that is use of SM and online marketing capabilities, moderate the relationship of SM engagement with purchase motivation. Practical implications This study discusses several practical implications for micro-firm marketing campaigns. First, it advises SM marketers and admins to focus more on creating content that develops differentiation about this particular firm's offerings compared to its competitors. This will bring clarity to customers' minds, leading to greater SM engagement. Second, SM teams with better digital capabilities can convert engaged users into loyal customers, leading to better firm performance in terms of purchases. Originality/value This is the first study to investigate the theoretical relationship between differentiation-oriented content and purchase motivation. Additionally, it contributes to existing knowledge by proposing firms' digital capabilities as moderators of the relationship between SM engagement and purchase motivation.
PurposeThe present study analyzes whether the compilation environmental, social and governance (ESG) framework as a complementary mechanism to the prevailing credit rating system has regulated earnings management (EM) practices in India during the ESG and non-ESG eras.Design/methodology/approachWe applied the Modified Jones and Roychowdhury models to estimate EM proxies. Fixed-effect panel regression was used to analyze the EM practices of 81 non-financial companies listed in the Nifty ESG 100 Index from 2013-2014 to 2023-2024 (891 firm-year observations).FindingsThe study found that credit rating is effective in reducing accrual earnings management (AEM), while ESG is effective in mitigating both AEM and total earnings management (TEM), whereas compilation of ESG as a complementary mechanism along with the existing CR mechanism is effective in mitigating AEM, real earnings management and TEM. Findings also reveal that firms used accounting accruals as a tool to signal their performance during the pandemic period.Research limitations/implicationsDue to the unavailability of data and limited implementation of the ESG framework, the present study is limited to large-cap non-financial companies. Also, the sector-wise impact of sustainable reporting has not been considered.Originality/valueTo the best of the authors' knowledge, this is the first study that analyzes the complementary effect of non-financial metrics (ESG) on financial metrics (CR) in regulating managerial discretionary practices in emerging markets like India, which is one of the fastest-growing sustainable investment avenues in the world.
PurposeThis study examines the impact of integrated paid, owned and earned media (POEM) on consumer purchase behavior and the moderating role of age in the online food ordering landscape.Design/methodology/approachThe study employs the S-O-R framework to propose a conceptual model of integrated POEM. Data were collected from consumers using online food aggregators, and analysis was conducted using structural equation modeling (SEM). The moderation analysis was performed using the PROCESS macro in SPSS.FindingsThe SEM analysis revealed a significant positive impact of POEM on brand awareness, which subsequently affects brand knowledge and purchase intention, ultimately shaping consumer purchase behavior. The moderation analysis indicates that age moderates the relationship between POEM and brand awareness.Practical implicationsPractically, the study provides actionable insights for marketers in online food ordering platforms by demonstrating the impact of integrated POEM on consumer purchase behavior. Each stage of this journey is critical for brands to manage effectively. Brands should monitor and optimize the transition from awareness to knowledge, intention and final purchase. Identifying gaps where conversions are not occurring is crucial. By tracking and analyzing each stage of the consumer journey, brands can gain valuable insights into where customers drop off, understand the reasons for these gaps and assess the effectiveness of their strategies. The moderation analysis highlights the need for age-specific strategies to optimize the effectiveness of POEM marketing communication.Originality/valueThis study is the first to explore the integrated POEM concept in the context of asset-light food aggregators using the S-O-R framework. It investigates the effects of POEM on consumer purchase behavior within food aggregator platforms and analyzes how age moderates the relationship between POEM and brand awareness. Thus, this research enhances the understanding of the complex dynamics in the online food delivery industry.
PurposeWith its superior analytical and decision-making capabilities, Artificial Intelligence (AI) is a valuable decision aid that enables organizational decision-makers to make effective and efficient decisions while reducing human errors. However, decision-makers continue to disproportionately rely on their intuition, especially when making decisions for ill-structured problems characterized by uncertainty and ambiguity. In this study, we assess the conditions in which decision-makers are willing to forego their intuition and rely on an AI decision aid for an ill-structured problem.Design/methodology/approachUsing a mixed-methods research design that included an experiment and an open-ended questionnaire, we assessed the conditions in which decision-makers are more likely to override their intuition and depend on an AI decision aid for an ill-structured decision.FindingsWe found that the decision-makers' reliance on the AI decision aid depended on two criteria: when the decision alternatives were similar rather than different, and when there was a considerable difference in the AI assessment of the decision alternatives. The qualitative analysis offered insights into the factors influencing participants' reliance on either their intuition or the AI decision aid.Originality/valueAI aversion is a significant issue for organizational development. The findings of this study increase our understanding of when and why decision-makers are more likely to rely on AI decision aids.
Purpose The core objective of the present research was to investigate the connection between digital financial literacy (DFL) and retirement planning (RP) and identify the role of saving behaviour (SB) as a mediator. The study explores how salaried individuals' financial knowledge of digital tools, combined with family and social influences, shapes their decision-making and impacts their digital financial well-being. Design/methodology/approach This study targeted employed individuals with regular salaries, using a quantitative approach to collect primary data via a questionnaire from 399 participants. Analytical methods, including descriptive analysis, parametric tests and reliability assessments, were applied using SPSS and Smart PLS 4.0 to ensure robust research outcomes. Findings In terms of digital financial behaviour, there were no discernible differences among employees from various socioeconomic backgrounds. DFL is strongly correlated with saving habits. Furthermore, there is a substantial positive connection between digital financial education and digital financial behaviour, particularly in the context of RP. It’s important to note that SB plays a role in partial mediation between DFL and RP. Originality/value This research represents the first attempt to explore the connection between DFL and RP, with SB as an intermediary factor, focusing on individuals who are employed and receive a salary.
Purpose Companies increasingly emphasize the importance of analytics software, including R programming, Tableau and advanced Excel skills. They expect college graduates to be proficient in these analytical tools. However, most colleges primarily teach basic Excel skills in lower-level courses, leaving advanced skillsets underexplored across different subject areas. This study investigates college students’ challenges and motivations related to learning advanced software skills. Design/methodology/approach Recognizing the fact that this study requires collection of perceptual data about various psychometric measures, we used survey instruments to measure participants’ perception. The unit of analysis is a college/graduate student who has taken an analytics course at the college. Data analysis was done through structural equation modeling, first through measurement model, and then structural model. Findings Our findings reveal that while college students recognize the demand for advanced analytics skills, they often lack full proficiency. Learning and using analytical tools can be daunting, leading to anxiety. Drawing on Dweck’s self-theories, our study explores factors influencing college students’ intentions to learn and use analytics software. We identify eight variables that impact this intention. This research contributes to data analytics education by highlighting potential gaps between students and employers regarding the demand for advanced analytics software skills. By understanding these factors, educators and institutions can better support students in developing proficiency in advanced analytics. Research limitations/implications First, our participants were exposed only to advanced Excel (spreadsheet) and Tableau (visual analytics). Given the variety of advanced analytics software, it would be a good idea for future researchers to examine students with analytics programming skills like R or Python. Second, we recruited survey participants only from business schools. Although there were some MBA students with different backgrounds, examining students who have to study advanced software in their specific disciplines will offer a richer ground for expanding this model. Practical implications This study highlights the challenges college students face in mastering data analytics skills. By leveraging self-theories and growth mindset theory, we identified key factors such as perceived usefulness and innovativeness that significantly influence students’ intentions to learn and use analytics software. Encouraging a growth mindset is essential for enhancing software adoption and utilization, with strategies focusing on effort, learning and improvement proving effective. Moreover, addressing software fatigue through addressing computer anxiety, adequate training and resource availability is crucial, thereby fostering a more conducive learning environment. Social implications In summary, this research informs educational practices, workforce readiness and the alignment of student skills with industry needs. It emphasizes the importance of fostering a growth-oriented mindset in students as they navigate the complexities of analytics software. Originality/value Given the highly demanded analytics skillset by employers, there is a paucity of research on how college students prepare for data analytics skillsets through advanced software. In this study we developed a model of college students’ use of advanced analytics software. Using the self-theories and the growth mindset theory, we theoretically investigate factors affecting college students’ behavioral intentions to learn and continue to use analytics software, in comparison with other general educational software skills. In our model eight variables are identified along with the three information processing dimensions, which explains 50.6% of the variance in using advanced analytics software.
PurposeAssociation to Advance Collegiate Schools of Business (AACSB) accreditation encourages business schools to exhibit alignment within their mission, strategies and outcomes to achieve success. The present study aims to explore the idea of mission alignment and how it may serve as an important moderator to the relationship between organizational resources and school performance as measured through business school rank.Design/methodology/approachOur study utilizes the AACSB International business school survey (BSQ) data to analyze the mission statements of accredited business schools and capture data on organizational resources. We also created an index of mission alignment to gauge congruency between the stated mission and strategic focus. Our performance measure was the U.S. News and World Report undergraduate business school programs ranking value.FindingsOur results show mission alignment on its own has little direct impact on organizational performance. However, when mission statement alignment and resource allocations are combined, they interact to influence organizational performance.Originality/valueOur research demonstrates that resource allocation decisions and mission alignment are two important attributes of an organization and that mission alignment has the potential to leverage an organization's resources and capabilities to improve performance.
PurposeThe purpose of this study is to test for the mediating effect of debt literacy in the relationship between microcredit access and the survival of micro, small and medium enterprises (MSMEs) owned and operated by young women in rural sub-Saharan Africa post COVID-19.Design/methodology/approachThis study uses a five-point Likert scale questionnaire to collect data from young women entrepreneurs with MSMEs located in rural northern Uganda. The Statistical Package for Social Sciences (SPSS) and SmartPLS with bootstrapping are used to test the magnitude and level of the mediation effect as recommended by Baron and Kenny (1986) and Hair et al. (2022).FindingsThe results reveal that debt literacy increases the impact of microcredit on the survival of young women entrepreneurs with MSMEs in rural sub-Saharan Africa post COVID-19 based on data collected from rural northern Uganda.Research limitations/implicationsA questionnaire was used to collect data for this study. Future studies could collect data using interviews and the experimental research design to evaluate the effect of debt literacy over time.Practical implicationsThis study provides valuable insights on the importance of debt literacy in microcredit access and the survival of MSMEs. The results of this study can be used to inform policy and guide practitioners on how to integrate debt literacy into the national educational and literacy curriculum.Originality/valueThis study brings into the limelight the important role of debt literacy in helping young women microentrepreneurs learn to be more cautious when taking on future debts and helping them become more resilient in the post COVID-19 pandemic situation. This topic of debt literacy is limited in the microcredit literature and the theory of microfinance in rural Uganda post COVID-19.
