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Various models and approaches are implemented to provide technical assistance and support to improve cocoa farmers' welfare in Ghana. The Farmer Business School (FBS), which is analogous to Farmer Field School (FFS), is one of the few initiatives of GIZ (Deutsche Gesellschaft für Internationale Zusammenarbeit) and Ghana Cocoa Board (COCOBOD). The main aim of the initiative is to train smallholder cocoa farmers to perceive cocoa production as a business. However, there is limited or conflicting evidence as to the effect of FBS on productivity and food security, especially in Ghana. This study assessed FBS participation and the participation's impact on productivity and food security of cocoa farmers.

The study used primary data collected from 542 cocoa farmers in Central and Western North regions of Ghana and employed descriptive statistics, perception index and Endogenous Switching Regression (ESR) as analytical tools.

The results, which reported an overall perception index of 0.7, indicated that the farmers had a strong positive perception on the FBS program. The results also showed that sex of a farmer, number of years of formal education, farm size, extension contact, perception, distance to extension outlet and membership of farmer-based organizations (FBOs) significantly influenced the decision to participate in FBS program. Also off-farm income, years of education and household size significantly influenced farm productivity and household food security. The results further showed that participation in FBS improved productivity and food security of cocoa farmers.

The study used data from two regions of Ghana, namely the Central region and the Western North region. Findings from studies using data covering all cocoa growing areas of Ghana could be more informative in formulating policies aimed at encouraging participation in FBS and consequently help improve cocoa productivity and food security.

This article offers insights into the welfare effects of FBS on cocoa farmers as previous similar studies are without this information.

In the past decade, the biopolymeric properties of chitosan (CH) have been largely exploited for various applications. This paper aims to study the use of CH in its nanoform, i.e. as nanofibers blended with polyvinyl alcohol (PVA) for various antimicrobial applications in detail. In particular, their ability toward bacterial growth inhibition, in vitro drug release and their biocompatibility toward tissue growth have been investigated in detail.

Electrospinning technique was adapted for depositing CH/PVA blended nanofilms on the silver foil under optimized conditions of high voltage. Three different concentrations of blended nanofiber samples were prepared and their antimicrobial properties were studied.

The bead diameter and average diameter of blended nanofibers increase with CH concentration. Antibacterial activity increases as CH concentration increases. Increased hydrophilicity in CH-enriched samples contributes to a higher drug release profile.

To the best of the authors’ knowledge, chick chorioallantoic membrane assay analysis has been carried out for the first time for CH/PVA films which shows that CH/PVA blends are biocompatible. CH after being converted as nanoparticles exhibits higher drug release rate by in vitro method.

This paper aims to analyse the character and strength of the claims made in an emerging literature offering a sociology of financial reporting principles.

The analysis evaluates exemplary works in the literature against the characteristics of the paranoid style first identified by Richard Hofstadter: overheated claims of a far-reaching, malign and collusive machinery of influence; a reductive, rationalistic and dualistic reading of events; weak empirics; and weak theorisation.

A significant stream within the literature is coming to be constructed in the paranoid style. Paranoid stylistics, used as a diagnostic tool, alerts us here to distorted judgement.

Alternative ways of avoiding the dangers of paranoid-style readings are suggested, ranging from resisting the temptations towards such readings to a radical re-working of the epistemics of “socio-accounting”.

The danger of allowing the conclusions advanced in the literature to go unchallenged is that they may influence society’s attitude to accounting, public policy-making and scholars’ willingness to contribute to the crafting of reporting principles and standards.

Although paranoid style analysis has been widely used to examine narratives in other academic fields, to the best of the author’s knowledge, this is the first study to apply it to scholarly accounting.

Sustainable manufacturing is one of the most important and most challenging issues in present industrial scenario. With the intention of diminish negative effects associated with cutting fluids, the machining industries are continuously developing technologies and systems for cooling/lubricating of the cutting zone while maintaining machining efficiency. In the present study, three regression based machine learning techniques, namely, polynomial regression (PR), support vector regression (SVR) and Gaussian process regression (GPR) were developed to predict machining force, cutting power and cutting pressure in the turning of AISI 1045. In the development of predictive models, machining parameters of cutting speed, depth of cut and feed rate were considered as control factors. Since cooling/lubricating techniques significantly affects the machining performance, prediction model development of quality characteristics was performed under minimum quantity lubrication (MQL) and high-pressure coolant (HPC) cutting conditions. The prediction accuracy of developed models was evaluated by statistical error analyzing methods. Results of regressions based machine learning techniques were also compared with probably one of the most frequently used machine learning method, namely artificial neural networks (ANN). Finally, a metaheuristic approach based on a neural network algorithm was utilized to perform an efficient multi-objective optimization of process parameters for both cutting environment.

Bayesian cubature (BC) has emerged to be one of most competitive approach for estimating the multi-dimensional integral especially when the integrand is expensive to evaluate, and alternative acquisition functions, such as the Posterior Variance Contribution (PVC) function, have been developed for adaptive experiment design of the integration points. However, those sequential design strategies also prevent BC from being implemented in a parallel scheme. Therefore, this paper aims at developing a parallelized adaptive BC method to further improve the computational efficiency.

By theoretically examining the multimodal behavior of the PVC function, it is concluded that the multiple local maxima all have important contribution to the integration accuracy as can be selected as design points, providing a practical way for parallelization of the adaptive BC. Inspired by the above finding, four multimodal optimization algorithms, including one newly developed in this work, are then introduced for finding multiple local maxima of the PVC function in one run, and further for parallel implementation of the adaptive BC.

The superiority of the parallel schemes and the performance of the four multimodal optimization algorithms are then demonstrated and compared with the k-means clustering method by using two numerical benchmarks and two engineering examples.

Multimodal behavior of acquisition function for BC is comprehensively investigated. All the local maxima of the acquisition function contribute to adaptive BC accuracy. Parallelization of adaptive BC is realized with four multimodal optimization methods.

Given the positive organizational principles associated with total quality management (TQM) – customer focus, continuous improvement, and process management – one would assume TQM's application is universally beneficial across businesses. Generally, research supports that notion. However, given resource limitations and shallow management teams in small businesses, there are multiple challenges in implementing TQM in small and medium-sized enterprises (SMEs). Therefore, small business leaders should benefit from knowledge linking other management practices to TQM’s positive effect on small firm performance, which enhances these leaders' return on TQM investment.

The authors apply partial least squares structural equation modeling (PLS-SEM) to explore TQM’s effect on small business performance and how other management practices enhance that relationship. Specifically, the authors explore how a comprehensive strategic approach (CSA) – a higher-order construct consisting of strategic planning, goal setting, and financial ratio analysis – moderates the relationship between TQM and small business performance. Given the complexity of the authors' model, the application of higher-order constructs, and the exploratory nature of this work, PLS-SEM is well suited for this study.

Consistent with prior research, the authors found that TQM (also a higher-order construct, consisting of seven lower-order constructs) positively impacts small firm performance. In addition, the authors found that CSA positively moderates the relationship between TQM and financial performance.

TQM’s effect on small business performance is enhanced when leaders implement a CSA. In other words, when small business leaders strategically plan, set goals, and analyze financial ratios, TQM's positive effect on firm performance is enhanced. This finding provides business leaders insights for how to maximize the TQM investment return.

This paper investigates the impact of family influence measured by the F-PEC scale on private enterprise (both family firms and lone founders) leadership succession strategy.

The research dataset is comprised of 390 private enterprises whose head offices were situated in the voivodeships of Lower Silesia and Wielkopolska in Poland. The authors collected data through CAPI (computer-assisted personal interviewing) method, as well as through comprehensive, structured interviews with company owners. Data were analysed using hierarchical logistic regression for each type of succession strategy.

The results suggest that increased family influence does not necessarily lead to intra-family leadership succession in private enterprises. Importantly, a range of findings contradicted authors' predictions. The relationship between the overall F-PEC scale values signifying the multi-faceted family influence over the business and the choice of internal successor was weakly negative for the total sample; also, the higher the overlap between family and business values and the higher the commitment to family business, as evidenced by the Culture subscale, the lower was the occurrence of intra-family successor choice in the population of lone founders. The Culture subscale also increased the prevalence of lack of succession planning in the sample of lone founders.

While several studies suggests that family firms may be more prone to choose an intra-family succession scenario, it remains unclear how lower levels of business and succession experience, may influence the successor choice. Indeed, some studies suggest that a strong family influence over a business, may stimulate family firms to choose a family outsider as a business leader. Therefore, the key contribution of this study is contextualizing the response to an ongoing succession debate. This study investigates the strategic choices of companies in the first generation of ownership operating in Poland, which serves as an example of a post-transition economy. While the characteristics of this economic environment may be unique, the authors discuss how the surprising findings may add to the understanding of the general succession processes present in private enterprises.

The present study assesses the commercial bank profit efficiency and its relationship to banking sector competition in a rapidly growing emerging economy, India from 2009 to 2019 using stochastic frontier analysis (SFA).

Lerner indices, conventional and efficiency-adjusted, quantify competition. Two SFA models are employed to calculate alternative profit efficiency (inefficiency) scores: the two-step time-decay approach proposed by Battese and Coelli (1992) and the recently developed single-step pairwise difference estimator (PDE) by Belotti and Ilardi (2018). In the first step of the BC92 framework, profit inefficiency is calculated, and in the second step, Tobit and Fractional Regression Model (FRM) are utilized to evaluate profit inefficiency correlates. PDE concurrently solves the frontier and inefficiency equations using the maximum likelihood process.

The results suggest that foreign banks are less profit efficient than domestic equivalents, supporting the “home-field advantage” hypothesis in India. Further, increasing competition drives bank managers to make riskier lending and investment choices, decreasing bank profit efficiency. However, this effect varies depending on bank ownership and size.

Literature on the competition bank efficiency link is conspicuously scant, with a focus on technical and cost efficiency. Less is known regarding the influence of competition on bank profit efficiency. The article is one of the first to examine commercial bank profit efficiency and its relationship to banking sector competition. Additionally, the study work represents one of the first applications of the FRM presented by Papke and Wooldridge (1996) and the PDE provided by Belotti and Ilardi (2018).

A switching depth controller based on a variable buoyancy system (VBS) is proposed to improve the performance of small autonomous underwater vehicles (AUVs). First, the requirements of VBS for small AUVs are analyzed. Second, a modular VBS with high extensibility and easy integration is proposed based on the concepts of generality and interchangeability. Subsequently, a depth-switching controller is proposed based on the modular VBS, which combines the best features of the linear active disturbance rejection controller and the nonlinear active disturbance rejection controller.

The controller design and endurance of tiny AUVs are challenging because of their low environmental adaptation, limited energy resources and nonlinear dynamics. Traditional and single linear controllers cannot solve these problems efficiently. Although the VBS can improve the endurance of AUVs, the current VBS is not extensible for small AUVs in terms of the differences in individuals and operating environments.

The switching controller’s performance was examined using simulation with water flow and external disturbances, and the controller’s performance was compared in pool experiments. The results show that switching controllers have greater effectiveness, disturbance rejection capability and robustness even in the face of various disturbances.

A high degree of standardization and integration of VBS significantly enhances the performance of small AUVs. This will help expand the market for small AUV applications.

This solution improves the extensibility of the VBS, making it easier to integrate into different models of small AUVs. The device enhances the endurance and maneuverability of the small AUVs by adjusting buoyancy and center of gravity for low-power hovering and pitch angle control.

This paper aims to examine the factors associated with a household business entrepreneur’s decisions to formalise the firm at a multidimensions level.

The data set is a panel of 2,336 SMEs and household businesses from Vietnamese SME surveys during the 2005–2015 period.

This study elucidates how firm-level resources, entrepreneur characteristics and costs of doing business influence an entrepreneur’s decision to enter, the speed and the degree of formality.

This study provides insight into the origins of an entrepreneur’s decisions to the multidimensions of business formality through the lenses of the resource-based view, entrepreneurship and institution theories.