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This study identified the determinants of improved rice variety adoption and measured their impact on farm productivity and the income of smallholder farmers in Indonesia.

We used a multistage sampling procedure and data from household surveys in four districts in the Banten region of Indonesia. An endogenous switching regression (ESR) model was used to estimate the impact of adoption, and the propensity score matching (PSM) non-parametric method tested the strength of the ESR findings.

The farm productivity of adoption increased by 11.45% and the income of smallholder farmers increased by 12.10% when compared to that of traditional methods.

The positive and significant effects of improved rice variety adoption indicated that research programs that develop improved rice varieties can optimize the productivity and income of smallholder farmers.

Adopting improved rice varieties increases the productivity and income of smallholder farmers, and the level of education, rice farming experience, access to extension workers, off-farm work, and mobile phone ownership have positive and significant effects on the adoption of improved rice varieties.

The purpose of this research is to conduct a theoretical prediction study exploring the effectiveness of different content marketing strategies in expanding the second-hand market for fashion brands, comparing the costs and risks involved in these strategies in practice.

First, the expert interview method is employed to extract the content marketing strategies of the fashion second-hand market. Then, a descriptive space that is able to identify various fashion brand images is established. Then, experts' perceptions of the relationships between content marketing strategies and fashion brand image dimensions are obtained through a subjective evaluation procedure. Data of semantic evaluation were quantified and analyzed using the fuzzy logic method.

When fashion brands expand to the second-hand market, they not only need to focus on improving the individual differentiation of products but also give priority to the quality of products and services and the overall customer experience. Exploring the “social impact strategy” will become an important direction for the development of fashion brands in the future.

The research methodology employed herein exhibits a noteworthy degree of novelty. This study introduces a pioneering theoretical prediction approach utilizing fuzzy logic, marking the inaugural exploration of this emerging and captivating dimension within the context of the study. Simultaneously, the study provides comparative results among content marketing strategies for expanding the fashion second-hand market, offering guidance for market expansion.

The aim of this research is to propose a quantitative approach to evaluating the quality of services provided, helping organizations to make strategic decisions by better understanding the characteristics that satisfy consumers.

The approach was based on the integration of the Kano model with SERVQUAL, adapted by the satisfaction equations of Albuquerque et al. (2022) and fuzzy systems theory. Through this, it was possible to infer which attributes influence customer satisfaction, identifying the ranges of satisfaction and, with the help of fuzzy, reducing the imprecision of customer perceptions.

A total of 42% of the attributes were classified as unidimensional, with attribute 11 (Reliability) and attribute 9 (Courtesy) having the highest satisfaction values. Attractive attributes accounted for 38% of the sample, with attribute 29 (Variety of products) and attribute 7 (Location) having the greatest impact on satisfaction. On the other hand, attribute 30 (Order Delay) and attribute 31 (Waiting for payment) caused more dissatisfaction among consumers (ranges −0.6, −0.71, respectively). In addition, Variety of products was the most satisfactory, while Order Delay generated the most dissatisfaction among users.

The originality of this research lies in its contribution to organizations in relation to the services offered by investigating a gap in the studies that use the Kano model, integrated with SERVQUAL, which do not include reverse attributes in their equations and analyses. With the help of fuzzy sets, the subjectivity of the individual can be translated into data for greater clarity of information.

The purpose of this paper is to evaluate the efficiency of a series network system with undesirable and unreturnable simultaneously.

The research was conducted by applying data envelopment analysis (DEA) approach to measure the efficiency score of a system and substages with an undesirable output of the second and third stages separately. For each case, new production technology was introduced, and based on them, novel DEA models were proposed.

One of the most important issues in the development of a country is the banking industry. In this study, 51 branches of commercial banks as a three-stage system with undesirable and unreturnable outputs in the second stage are considered. Then, the efficiency of each branch and substages is measured by using proposed models.

The efficiency of a three-stage network in the presence of undesirable and unreturnable outputs was assessed. In this model, Kousmanen’s technology was used.

The purpose of this paper is to establish a maturity evaluation model for the application of construction steel structure welding robotics suitable for the actual situation and specific characteristics of engineering projects in China and then to assess the maturity level of the technology in the application of domestic engineering projects more scientifically.

The research follows a qualitative and quantitative analysis method. In the first stage, the structure of the maturity model is constructed and the evaluation index system is designed by using the ideas of the capability maturity model and WSR methodology for reference. In the second stage, the design of the evaluation process and the selection of evaluation methods (analytic hierarchy process method, multi-level gray comprehensive evaluation method). In the third stage, the data are collected and organized (preparation of questionnaires, distribution of questionnaires, questionnaire collection). In the fourth stage, the established maturity evaluation model is used to analyze the data.

The evaluation model established by using multi-level gray theory can effectively transform various complex indicators into an intuitive maturity level or score status. The conclusion shows that the application maturity of building steel structure welding robot technology in this project is at the development level as a whole. The maturity levels of “WuLi – ShiLi – RenLi” are respectively: development level, development level, between starting level and development level. Comparison of maturity evaluation values of five important factors (from high to low): environmental factors, technical factors, management factors, benefit factors, personnel and group factors.

In this paper, based on the existing research related to construction steel structure welding robot technology, a quantitative and holistic evaluation of the application of construction steel structure welding robot technology in domestic engineering projects is conducted for the first time from a project perspective by designing a maturity evaluation index system and establishing a maturity evaluation model. This research will help the project team to evaluate the application level (maturity) of the welding robot in the actual project, identify the shortcomings and defects of the application of this technology, then improve the weak links pertinently, and finally realize the gradual improvement of the overall application level of welding robot technology for building steel structure.

Previous studies have rarely integrated the financing modes of a capital-constrained manufacturer with the choices of online sales strategies. To address this gap, the authors study how a manufacturer selects optimal financing modes under different sales strategies in three dual-channel supply chains.

This paper considers three sales strategies, namely, combining a traditional retailer channel with one of the direct selling, reselling and agency selling channels, and two common financing modes, namely, bank financing and retailer financing. The authors obtain equilibrium outcomes of the manufacturer and traditional retailer and then provide the conditions for them to select optimal financing modes under three sales strategies.

The results indicate that the manufacturer’s financing decisions rely on the initial capital and interest rates, and the manufacturer selects retailer financing only if the initial capital is relatively larger. In terms of financing mode options, the retailer financing mode is more beneficial for the manufacturer under the three sales strategies. From the perspective of sales strategies, the direct selling model is more beneficial. In addition, the higher the consumer acceptance of the online channel, the more profits the manufacturer obtains.

This paper provides suggestions on how the capital-constrained manufacturer chooses financing modes and sales strategies.

This paper integrates the financing mode and different sales strategies to investigate the manufacturer’s optimal operational decisions. These sales strategies allow us to investigate the manufacturer’s optimal financing modes in the presence of both different financing modes and sales strategies.

The paper assesses the role of natural resource rents in Nigeria's economy through the channel of institutional quality.

The analysis is done with the use of autoregressive-distributed lag (ARDL) bounds testing approach to cointegration, vector error correction model (VECM), Granger causality test and cointegrating regression over the period 1996–2019.

Findings support the notion that overreliance on natural resources could exacerbate the growing number of dysfunctional economic outcomes in the country. The study confirms that a mix of weak governance quality and natural resource rents could have a negligible effect on economic growth and possible retardation impact on the economy in the long run as well as in the short run. The evidence further reveals that there is unidirectional causality running from the interaction term to growth, suggesting that growth trajectory could be jointly determined by natural resource rents and the quality of institutions.

The divergent arguments associated with the mechanisms of resource curse in each of the resource-rich countries offer ample support for the contention that economic outcomes in resource-abundant states may not be a product of resource windfalls per se, but rather the quality of governance or ownership structure. Hence, the ultimate aim of the analysis is to further understanding on the link between resource rents and growth in Nigeria via governance channel.

This paper aims to investigate the effect of corporate environmental disclosure on earnings management and to further examine whether this relationship is moderated by female board.

Our sample includes 264 European companies listed on the STOXX eUROPE 600 for the period 2010 to 2022. We excluded financial companies (banks and insurance companies) due to their specific capital structure and regulatory requirements, and companies with missing data. Feasible Generalized Least Square (FGLS) regression method is used to estimate the econometric models. For robustness analyses, the authors included the alternative measure of the dependent variable, and they applied the simultaneous equation model for the endogeneity test.

Using discretionary accruals as a proxy for earnings management, the results obtained indicated a negative effect of corporate environmental disclosure on earnings management. The results suggest also that women on boards are effective in their monitoring role. Indeed, findings show that the effect of corporate environmental disclosure on earnings management is particularly stronger with the presence of women directors on the companies’ boards.

This study has two limitations. Firstly, the sample size is relatively small, which may limit the generalizability of our findings. Secondly, our earnings management indicator, based on estimates of accruals, may not perfectly reflect all streams of earnings management. Therefore, to reduce potential bias in these estimates, it would be useful to use other indicators, such as real earnings management.

The findings have several implications for regulatory, investors and academic researchers. For regulators, it is appropriate to promote several standards related to corporate environmental disclosure and earnings management. The results advise also the worldwide policy maker to give the importance of female roles to improve engagement firms in corporate environmental disclosure, so to be more transparent in their accounting practices to ensure that they are not engaging in unethical or fraudulent behavior. For investors, the results show that the existence of female directors on the board reduces earnings management. For academic researchers, it is interesting to explore the relationship between corporate environmental disclosure, women on the board, and earnings management.

This paper extends the existing literature by examining the moderating effect of women directors on the relationship between corporate environmental disclosure and earnings management in the European context.

This paper aimed to shed light on the relationship between blockchain technology intensity and tax evasion and whether this relationship is moderated by good governance.

Data from a sample of 50 European companies selected from the STOXX 600 index between 2010 and 2019 were used to test the model via panel data and multiple regression. Here, we used the generalized least squares method estimated on panel data. A multivariate regression model was used to analyze the moderating effect of good governance on the association between blockchain technology intensity and tax evasion. For the robustness analyses, we included the comparative study of legal systems. We performed an additional analysis by testing the dynamic dimension of the data set using the generalized method of moments to control for the endogeneity problem.

Expectedly, the results showed a negative relationship between blockchain technology intensity and tax evasion. Furthermore, the findings suggest that the moderating variable negatively affects the relationship between blockchain technology and tax evasion.

To our knowledge, this study supports the existing literature. Firstly, it expands the scientific debate on tax evasion. Secondly, it extends the scope of the agency theory, which is used to explain the phenomena associated with tax evasion. This study is one of the first to examine the moderating effect of good governance on the association between blockchain technology intensity and tax evasion.

We introduce decision support tools aimed at optimizing perishable food supply chain management, effectively balancing conflicting objectives such as the exporter’s product collection cost and the importer’s profit. This involves considering factors like perishability, selling price, discount rate, and order quantity to achieve optimal outcomes.

This study considered a three-echelon supply chain comprising farmers, a single exporter, and a single importer providing a single, random-lifetime, perishable product under deterministic customer demand. The proposed mathematical model derived the optimal order quantity, selling price, and discount rate for the entire supply chain. This integrated optimization model treats both demand and supply sides as a multi-objective problem, employing a nonlinear program and a two-stage capacitated vehicle routing problem formulation. Numerical examples and a case study focusing on Thailand durian supply chain were conducted to illustrate the approach of the proposed model.

Taking into account both the importer’s profit and the exporter’s product collection cost, the proposed integrated supply chain model and tools maximize profitability, minimizes waste, and meets demand by optimizing perishable product collection costs and proposing a discount system for selling prices.

Limited to a single perishable product in a three-echelon international food supply chain. Future research can explore different products and supply chain contexts.

The tools enhance decision-making for supply chain managers, improving efficiency, reducing costs, and enhancing customer satisfaction in the perishable food industry.

The proposed model aids in local workforce management by forecasting required manpower for upcoming seasons. By factoring in product quality and pricing, it ensures customers receive fresh products at fair prices. Furthermore, the near-zero waste concept enhances storage conditions at importers' facilities, contributing to improved environmental hygiene.

The integrated model and decision support tools offer a novel approach to address complexities and conflicting objectives in perishable food supply chains, providing practical insights for researchers and practitioners.