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This study analyzes how tech firms can implement the modern wave of subscription-based business model (SBBM), including value proposition, value creation, value capture and performance. In fact, these elements push tech firms to move from traditional to SBBMs.

To achieve the objectives of this study, we initially construct a theoretical framework for applying SBBM. Subsequently, we employ qualitative research to examine the current implementation of the subscription-based economy within tech firms.

A successful SBBM necessitates capturing value through sustainable revenue transactions and revising aspects of the value proposition, creation and capture. Continuous improvement through business value analysis is imperative. Additionally, an agile operations system is vital to address revenue complexities, enable data collection and enhance value proposition, service innovation, churn rate and customer retention, which are essential for SBBM maintenance.

This study delves into how the subscription-based economy is reshaping the business models of tech firms. Beyond exploring the theoretical foundation of this transformative path, this study offers actionable insights on enhancing the value proposition, creation, capture and business value within subscription-based economy frameworks.

The authors examine the impact of audit quality (AQ) on classification shifting (CS) among non-financial firms operating in the UK and Germany.

This paper used various audit committee variables (size, meetings, gender diversity and financial expertise) to measure AQ and its impact on CS. The authors used a total of 2,110 firm-year observations from 2010 to 2019.

The authors found that the presence of female members on the audit committee and audit committee financial expertise deter the UK and German managers from shifting core expenses and revenue items into special items to inflate core earnings. However, audit committee size is positively related to CS among German firms but has no impact on UK firms. The authors also document evidence that audit committee meetings restrain UK managers from engaging in CS. However, the authors found no impact on CS among German firms. The study results hold even after employing several tests.

Overall, the study findings provide broad support in an international setting for the board to improve its auditing practices and offer essential information to investors to assess how AQ affects the financial reporting process.

Most CS studies used market-oriented economies such as the USA and UK and ignored bank-based economies such as Germany, France and Japan. The authors provide a comparison among bank and market-oriented economies on whether the AQ has a similar impact on CS or not among them.

This study aims to investigate earnings management practice of classification shifting of revenues in Chinese-listed firms.

The study employs a dataset of 2,920 A-listed firms from Chinese stock exchanges of Shanghai and Shenzhen for the period of 2003–2019. We apply both univariate and panel regression analysis by using fixed effect estimation with robust standard errors.

Our findings reveal that firms misclassify revenues by taking advantage of the flexibility provided by applicable financial reporting standards. The empirical evidence obtained through regression analysis suggest that managers reclassify non-operating revenues as operating revenue to alter the economic reality while seeking the advantage of financial reports users’ vulnerability for valuing the upper half of income statement items more as compared to lower part. The results further indicate that international financial reporting standards adoption inhibits the earnings management practices using classification shifting of revenues. It is also concluded that firms, which are suffering losses or having low growth, are more persistently involved in misclassification of revenues.

The study is unique from the point of view that it investigates earnings management from the prospective of revenue’s classification in an emerging market characterized by various market imperfections such as lower investor protection and higher information asymmetry.

This study aims to investigate the role of three customer equity drivers on customer repurchase intent in business-to-business (B2B) markets. It also explores the interconnected nature of equity drivers, specifically, the effects of brand equity and value equity on relationship equity. Further, it investigates how perceived switching costs moderates the interrelationships between customer equity drivers. The authors explore the interrelationships between the customer equity drivers in a B2B context involving commodity products in a developing market.

Data collection was done from a pool of 184 institutional customers of a lubricant brand in a developing market. The sample had representations of buyer organizations across sectors, namely, automobile, cement, metal, fertilizer, railway, defence and mining, etc. The final data were subjected to partial least squares-based structural equation modeling to test the hypothesized model.

The study found a direct effect of brand equity, and value equity on relationship equity and an indirect effect on repurchase intent, namely, relationship equity. Perceived switching cost was found to moderate the interaction between brand equity and relationship equity as well as between value equity and relationship equity. The direct effect of relationship equity on repurchase intent was also significant.

The study implies that B2B firms should ground their marketing program on these customer equity drivers, especially when dealing with commodity products. The absence of any of these drivers would be detrimental in customer retention. The study also establishes the relevance of switching cost(s) and its impact on the underlying dynamics between the different equity drivers in the context of commodity products. The customer equity drivers along with switching costs, if managed well, may become switching barriers for customers and eventually would ensure recurring revenue through repeat purchases.

To the best of the authors’ knowledge, this is one of the first studies that focuses on the disaggregated effect of customer equity on customer outcomes in the B2B context. Furthermore, this study investigates how perceived switching costs moderates the interrelationships between customer equity drivers in the industrial sales context in an emerging market.

This study aims to synthesize and integrate findings from diverse research on the antecedents and moderators of customer loyalty in the banking sector. Through a comprehensive meta-analysis, the research seeks to understand the primary drivers of bank loyalty and the potential cultural, economic and social indicators that might influence these relationships.

A rigorous meta-analysis was conducted, analyzing 275 studies with 1,365 effect sizes involving over 134,000 bank customers from more than 50 countries. The research evaluated the effect sizes of the main relationships between loyalty antecedents and consequences and assessed the influence of cultural, economic and social moderators.

The study identified key antecedents of bank loyalty, with responsiveness, privacy, commitment, trust and empathy being paramount. Cultural dimensions, such as individualism and masculinity, significantly moderate the relationships between trust and loyalty. The human development index (HDI) was also identified as a significant economic moderator, particularly influencing the relationship between satisfaction and bank loyalty.

This research offers a holistic view of bank loyalty, bridging gaps from conflicting findings in prior literature. Examining a vast array of studies across diverse cultural and economic contexts provides empirical generalizations about bank loyalty behavior, offering valuable insights for academia and the banking industry.

This study aims to propose and assess a model with the main elements influencing Brazilian agtech scalability with the aim of supporting the scalability process of startups that find themselves in the stage of initial conception of the business model.

The research was conducted using the design science research (DSR) method. The data for assessing the proposed model were collected through in-depth interviews. The answers were analyzed quantitatively, using descending hierarchical classification (DHC), correspondence factor analysis (CFA), and level of agreement; and qualitatively, using content analysis.

Considering the Brazilian context, the objective, environmental, structural, and evaluative dimensions presented positive characteristics for the main criteria analyzed (operational viability, generality, clarity, adaptation to the reality studied, completeness, consistency, comprehensibility, and structural simplicity). Specific improvements were proposed in all the criteria analyzed.

The artifact can be considered a strategic guide for agtechs that have yet to overcome the barrier of initial conception of the business model. The model enables the identification of the main problems that agtechs can encounter in their life cycle, as well as seeking solutions in advance.

The study examines the influence of a firm's life cycle on the cash flow classification of Indian firms.

The study employs Dickinson's (2011) cash flow patterns to classify firm years under various life-cycle stages. Cash flow classification is employed to measure a firm's classification shifting (CS) practices. The study includes Indian firms listed on the Bombay Stock Exchange during 2012–2020, an ordinary least squares regression model, a fixed-effect model and a panel corrected with standard error regression method.

Firms face different opportunities and challenges at different stages of the firm's life cycle and therefore adopt cash flow CS. The results show that firms adopt cash flow CS during introduction, growth and decline stage of life cycle either to boost or to reduce operating cash flows.

This study is one of its kind to study the influence of a firm's life cycle on the cash flow classification of Indian firms.

E-commerce companies use different types of dark patterns to manipulate choices and earn higher revenues. This study aims to evaluate and prioritize dark patterns used by e-commerce companies to determine which dark patterns are the most profitable and risky.

The analytic hierarchy process (AHP) prioritizes the observed categories of dark patterns based on the literature. Several corporate and academic specialists were consulted to create a comparison matrix to assess the elements of the detected dark pattern types.

Economic indicators are the most significant aspect of every business. Consequently, many companies use manipulative methods such as dark patterns to boost their revenue. The study revealed that the revenue generated by the types of dark patterns varies greatly. It was found that exigency, social proof, forced action and sneaking generate the highest revenues, whereas obstruction and misdirection create only marginal revenues for an e-commerce company.

The limitation of the AHP study is that the rating scale used in the analysis is conceptual. Consequentially, pairwise comparisons may induce bias in the results.

This paper suggests methodical and operational techniques to choose the priority of dark patterns to drive profits with minimum tradeoffs. The dark pattern ranking technique might be carried out by companies once a year to understand the implications of any new dark patterns used.

The advantages of understanding the trade-offs of implementing dark patterns are massive. E-commerce companies can optimize their spent time and resources by implementing the most beneficial dark patterns and avoiding the ones that drive marginal profits and annoy consumers.

The purpose of this paper, therefore, is to amplify the imperativeness for a re-oriented regulatory approach that prioritizes constructive engagement with the regulated communities, harnessing the existing pool of savings and retention of market participation.

The paper adopts a doctrinal legal research design with data drawn from primary and secondary sources of law. The primary sources include case laws and statutes, and the secondary sources include book chapters, journal articles and other internet-sourced materials.

The paper finds that the status quo in Nigeria if left to continue would spell severe economic disaster for Nigeria’s securities administration, but a well-structured realignment of the regulations would boost the country’s securities market effectiveness.

The research’s conclusions and suggestions might only be applicable to Nigeria’s particular situation with regard to capital market development and securities regulation. Other nations or locations with distinct regulatory systems, market structures and economic situations may not be able to immediately adapt it. When extending the research results outside of the Nigerian environment, caution should be exercised. For regulatory agencies and policymakers, the research offers insightful suggestions. The analysis may pinpoint certain areas where policy changes are required to address reoccurring problems and improve the chances for a healthy capital market.

For Nigeria’s regulatory frameworks controlling securities to be strengthened, this paper would be crucial. To make sure they are in line with global best practices, this entails examining and revising current laws, rules and standards. A stronger regulatory environment may also result from the implementation of harsher enforcement procedures and consequences for noncompliance. It is also required for creating market infrastructure, fostering market integration and cooperation, facilitating access to capital, monitoring and evaluation. It would also benefit investor education and protection.

Addressing these persistent issues and potential remedies in Nigeria’s capital market development and securities regulation would have various advantageous social effects. These include improved market infrastructure, more financial inclusion, improved investment protection for investors and improved market openness and integrity. Such results will help Nigerian society as a whole by fostering economic expansion, job creation, wealth distribution and general social progress.

This paper is the original work of the authors and has not been published anywhere nor submitted to another journal for publication.

This study aims to explore the use of time series analyses to examine changes in travelers’ preferences in accommodation features by disentangling seasonal, trend and the COVID-19 pandemic’s once-off disruptive effects.

Longitudinal data are retrieved by online traveler reviews (n = 519,200) from the Canary Islands, Spain, over a period of seven years (2015 to 2022). A time series analysis decomposes the seasonal, trend and disruptive effects of six prominent accommodation features (view, terrace, pool, shop, location and room).

Single accommodation features reveal different seasonal patterns. Trend analyses indicate long-term trend effects and short-term disruption effects caused by Covid-19. In contrast, no long-term effect of the pandemic was found.

The findings stress the need to address seasonality at the single accommodation feature level. Beyond targeting specific features at different guest groups, new approaches could allow dynamic price optimization. Real-time insight can be used for the targeted marketing of platform providers and accommodation owners.

A novel application of a time series perspective reveals trends and seasonal changes in travelers’ accommodation feature preferences. The findings help better address travelers’ needs in P2P offerings.