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The purpose of the study is to estimate the willingness to pay (WTP) for major chemical fertilizers and revisit the fertilizer subsidy policy in Nepal.

We surveyed 619 households from six districts and assessed farmers’ WTP for urea, diammonium phosphate (DAP) and muriate of potash (MOP) during the fertilizer crisis. Our study elicited the WTP for fertilizers when fertilizers were not available on the market. A modified payment card approach was used to elicit farmers’ WTP.

The study found that farmers who buy fertilizer from agrodealers, buy from gray markets, have bank accounts, are willing to take a risk, have strong or medium economic conditions and incur higher travel costs have a higher WTP for fertilizers. Farmers in sampled areas, on average, are willing to pay 31 percent more for urea, 13 percent more for DAP and 19 percent more for MOP than the government recommended fertilizer price.

The design of the payment card and the estimation techniques used to fit the valuation function are likely to influence WTP.

Overall, literature on households’ WTP for fertilizers in developing countries is scarce. Our study contributes to the knowledge of WTP for fertilizers.

E-commerce companies often manipulate customer decisions through dark patterns to meet their interests. Therefore, this study aims to identify, model and rank the enablers behind dark patterns usage in e-commerce companies.

Dark pattern enablers were identified from existing literature and validated by industry experts. Total interpretive structural modeling (TISM) was used to model the enablers. In addition, “matriced impacts croisés multiplication appliquée á un classement” (MICMAC) analysis categorized and ranked the enablers into four groups.

Partial human command over cognitive biases, fighting market competition and partial human command over emotional triggers were ranked as the most influential enablers of dark patterns in e-commerce companies. At the same time, meeting long-term economic goals was identified as the most challenging enabler of dark patterns, which has the lowest dependency and impact over the other enablers.

TISM results are reliant on the opinion of industry experts. Therefore, alternative statistical approaches could be used for validation.

The insights of this study could be used by business managers to eliminate dark patterns from their platforms and meet the motivations of the enablers of dark patterns with alternate strategies. Furthermore, this research would aid legal agencies and online communities in developing methods to combat dark patterns.

Although a few studies have developed taxonomies and classified dark patterns, to the best of the authors’ knowledge, no study has identified the enablers behind the use of dark patterns by e-commerce organizations. The study further models the enablers and explains the mutual relationships.

The authors examine the determinants of ESG disclosure and differentiate between voluntary and mandatory disclosure regimes in Hong Kong.

The authors analyse both Bloomberg ESG scores and a disclosure index score, manually constructed according to the 2019 Hong Kong Exchange ESG Guide using regression tests.

The results indicate that the level of concentrated ownership is negatively associated with the quantity of ESG disclosure only in the voluntary disclosure period, suggesting that agency problems are alleviated when ESG reporting is mandatory. The findings also show that larger firms significantly disclose higher levels of ESG information in both voluntary and mandatory disclosure periods. Furthermore, the extent of ESG disclosure significantly increases when firms' sustainability reports are audited by Big 4 accounting firms only in the voluntary disclosure period. Finally, the control variables are significantly related to the level of ESG disclosure showing that ESG disclosure increased over time and is significantly different among industries.

The authors make contributions to the literature on non-financial disclosure in relation to ESG reporting by examining the relationship between firm characteristics and ESG disclosure in the Hong Kong context under both voluntary and mandatory disclosure regimes. This study also provides important implications for other stock markets and relevant stakeholders including preparers, users and the sustainability profession.

This study aims to examine investors' reactions to bad financial news (IRBFN) based on complex financial accounting disclosures (CFAD) as well as how investors' herding behavior influences investor reactions in United Arab Emirates (UAE) project-based organizations (PBOs).

The primary data collection was furnished via online questionnaires, and 310 completed questionnaires were analyzed using structural equation modelling (SEM), moderation analysis, multiple regression simulations and path analysis.

The study shows that four out of the five CFAD dimensions observed – investors’ relations (IR), board and management structure, transparency disclosure and other disclosure channels – have a direct influence on investor's reactions to bad financial news, with the exception of “external auditing and audit service”. In addition, investor herding has a moderation impact on the relationship between CFAD and IRBFN.

There is a possibility that the broad view of the results may be limited by the size of the research sample. The paper's findings should therefore be authenticated at an intercontinental level with the same conceptual framework in other nations.

The purpose of modeling stakeholders' decision-making process is to improve their decisions and to control their reactions that may negatively affect PBOs in the UAE.

This research contributes to planned behavior theory and agency theory in the UAE context, both of which are empirically tested.

The purpose of the study is to investigate the factors that influence the adoption of new sustainability reporting (SDG) and external assurance (EXTA) practices. This study also examines the relationship between sustainability reporting activity and corporate economic performance for a sample of 99 companies in Gulf Cooperation Council (GCC) countries that addressed SDGs in their sustainability reports published in 2019.

Using a two-stage analysis, this study examines how firms’ characteristics and corporate governance variables affect SDG and economic performance, as well as the firm’s decision to adopt EXTA statements for a sample of companies in that addressed SDGs in their sustainability reports published in 2019. The authors collected data from the Global Reporting Initiative’s (GRI) Sustainability Disclosure database and the Bureau van Dijk for Orbis database.

The results show that the variables firm size, profitability, big 4 auditors and government ownership significantly affect SDG and economic performance. The results also reveal that firms operating in the manufacturing sector are positively correlated with SDG and the firm’s decision to adopt EXTA statements. Furthermore, the results indicate that board independence positively affects SDGs and EXTA.

The results can be particularly relevant and timely in helping large GCC companies promote their engagement to sustainable development practices by adopting more sustainable long-term strategies and policies. The findings could also guide managers in the strategic direction to identify firms’ characteristics and corporate governance features essential to promote sustainability reporting, an increasingly important performance indicator for investors and to enhance their confidence in the capital market. The results may also have practical implications to policymakers and other regulators in GCC countries to define effective frameworks that promote sustainable development reports and the use of EXTA.

The results make significant contributions by providing new insights to the existing literature on sustainability reporting in emerging markets by examining a unique perspective on the influence of firms’ characteristics and corporate governance features on the adoption of new sustainability reporting practices. The authors further add to the previous literature on the relationship between a firm’s economic performance and sustainable reporting by providing evidence from large companies in GCC countries, which might benefit from the adoption of multiple conceptual lenses, in this case, legitimacy and stakeholder theories. Lastly, through the empirical findings, this study provides economic validity to the 2018 joint initiative of the GRI and the United Nations Global Compact to strengthen corporate actions to achieve the United Nations SDGs.

This study assesses the extent to which integrated extension services contribute to the adoption of climate-smart agriculture (CSA) innovations within the cotton value chain in Burkina Faso.

To address the research question, a probit multivariate econometric model with sample selection is utilized. The model is applied to a random sample of farmers (n = 510), and the endogeneity is addressed through a control function approach.

The study highlights the central role of value chains, particularly in the cotton sector, in overcoming resource scarcity through integrated extension services. Findings show that smallholder farmers who benefit from sound extension services are more willing to adopt and diversify CSA technologies. These include improved seeds, conservation techniques, adapted planting dates and mechanization. This study confirms the synergistic nature of these technologies and emphasizes that effective climate risk mitigation depends on the combined adoption of CSA technologies.

The use of cross-sectional data limits the analysis of long-term farmer behavior, and due to data limitations, the focus was primarily on the contributions of cotton companies and farmers to climate risk mitigation. Future research using panel data across the value chain could provide a more robust insights for policy decision-making.

The study contributes to the existing body of knowledge by emphasizing the crucial role of integrated extension services within the cotton value chain in developing countries. This highlights the critical benefits for farmers and emphasizes the need to diversify modern technologies to effectively combat climate change and its variability in agriculture.

Given the regional heterogeneity of economic development, electricity consumption in various regions exhibits a discrepant growth pattern. The purpose of this study is to construct a grey system forecasting model with intelligent parameters for predicting provincial electricity consumption in China.

First, parameter optimization and structural expansion are simultaneously integrated into a unified grey system prediction framework, enhancing its adaptive capabilities. Second, by setting the minimum simulation percentage error as the optimization goal, the authors apply the particle swarm optimization (PSO) algorithm to search for the optimal grey generation order and background value coefficient. Third, to assess the performance across diverse power consumption systems, the authors use two electricity consumption cases and select eight other benchmark models to analyze the simulation and prediction errors. Further, the authors conduct simulations and trend predictions using data from all 31 provinces in China, analyzing and predicting the development trends in electricity consumption for each province from 2021 to 2026.

The study identifies significant heterogeneity in the development trends of electricity consumption systems among diverse provinces in China. The grey prediction model, optimized with multiple intelligent parameters, demonstrates superior adaptability and dynamic adjustment capabilities compared to traditional fixed-parameter models. Outperforming benchmark models across various evaluation indicators such as root mean square error (RMSE), average percentage error and Theil’s index, the new model establishes its robustness in predicting electricity system behavior.

Acknowledging the limitations of traditional grey prediction models in capturing diverse growth patterns under fixed-generation orders, single structures and unadjustable background values, this study proposes a fractional grey intelligent prediction model with multiple parameter optimization. By incorporating multiple parameter optimizations and structure expansion, it substantiates the model’s superiority in forecasting provincial electricity consumption.

This paper aims to explore how historical context influences the content and selection of rhetorical legitimation strategies. Using case study method, this paper will focus on how insurance companies and labor tried to defend their legitimacy in the context of enactment of Medicare in the USA. What factors influenced the strategic (rhetorical) decisions made by insurance companies and labor unions in their institutional work?

The study is empirically grounded in archival research, involving an analysis of over 9,000 pages of congressional hearings on Medicare covering the period 1958–1965.

The authors show that rhetorical legitimation strategies depend significantly on the specific historical circumstances in which those strategies are used. The historical context lent credibility to certain arguments and organizations are forced to decide either to challenge widely held assumptions or take advantage of them. The authors show that organizations face strong incentives to pursue the latter option. Here, both the insurance companies and labor unions tried to show that their positions were consistent with classical liberal ideology, because of high respect of classical liberal principles among different stakeholders (policymakers, voters, etc.).

It is uncertain how much the results of the study could be generalized. More information about the organizations whose use of rhetorics the authors studied could have strengthened our conclusions.

The practical relevancy of the revised paper is that the authors should not expect hegemony challenging rhetorics from organizations, which try to influence legislators (and perhaps the larger public). Perhaps (based on the findings), this kind of rhetorics is not even very effective.

The paper helps to understand better how organizations try to advance their interests and gain acceptance among the stakeholders.

In this paper, the authors show how historical context in practice influence rhetorical arguments organizations select in public debates when their goal is to influence the decision-making of their audience. In particular, the authors show how dominant ideology (or ideologies) limit the options organizations face when they are choosing their strategies and arguments. In terms of the selection of rhetorical justification strategies, the most pressing question is not the “real” broad based support of certain ideologies. Insurance company and labor union representatives clearly believed that they must emphasize liberal values (or liberal ideology) if they wanted to gain legitimacy for their positions. In existing literature, it is often assumed that historical context influence the selection of rhetorical strategies but how this in fact happens is not usually specified. The paper shows how interpretations of historical contexts (including the ideological context) in practice influence the rhetorical strategies organizations choose.

Given the importance of the growing segmentation of ageing consumers and their increasing interaction with the Internet, digital marketing scholars are becoming more interested in this market. Prior research needs to pay more attention to this market in many contexts of digital marketing. This study aims to provide insights into ageing consumers’ content usage, content typology choices, and online brand advocacy (OBA).

Semi-structured interviews were applied, and 16 consumers from Southern Europe aged 55+ were included. The interviews were transcribed and examined following the principles of content analysis.

According to the research, older consumers display their usage and concerns regarding online content. They have different decision-making processes depending on whether they are purchasing products or services. Likewise, their choices of content typology vary based on the utilitarian or hedonic product category.

This study contributes to the literature by providing insights into this growing segmentation and proposing an OBA framework for older consumers related to content marketing. Finally, the study suggests that older consumers are passive online and active offline brand advocates.

Access to financing is a key success factor for start-ups. High failure rates, long payback periodse and asymmetries lead to conservative pricing and valuation discounts. The authors examine financial marketing and contingent factors, as enablers of a “patent premium” by private equity (PE) investors targeting start-ups in their growth and expansion stages.

Drawing from the contingency, innovation and signaling theories, the authors collect patent records for Italian start-ups in which a higher than 30% stake was acquired by PE investors during the period 2014–2020. The authors apply a generalized linear model with a logit link and robust clustered error to test the key relationships and control for endogeneity with a Heckman two-stage selection model.

Findings indicate start-ups’ access to financing is significantly impacted by marketing constructs adopted in the operation. Innovation alone does not suffice to determine a valuation premium, unless contingent on the promotion of its product, the placement -investors targeted-of the equity, brand equity levers of previous ownership and marketing competence backing the deal.

The authors provide new insights in the marketing-finance interface, highlighting levers that reassure investors and enable monetizing innovation in start-ups that are still privately held. The authors bridge a gap in literature that has mainly focused on venture capital and innovation financing in the open market, as well as a significant gap regarding the marketing design of private equity placements.