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The purpose of this paper is to generalize the traditional risk evaluation methods and to specify a multi-level risk evaluation framework, in order to prepare customized risk evaluation and to enable effectively integrating the elements of risk evaluation.

A real case study of an electric motor manufacturing company is presented to illustrate the advantages of this new framework compared to the traditional and fuzzy failure mode and effect analysis (FMEA) approaches.

The essence of the proposed total risk evaluation framework (TREF) is its flexible approach that enables the effective integration of firms’ individual requirements by developing tailor-made organizational risk evaluation.

Increasing product/service complexity has led to increasingly complex yet unique organizational operations; as a result, their risk evaluation is a very challenging task. Distinct structures, characteristics and processes within and between organizations require a flexible yet robust approach of evaluating risks efficiently. Most recent risk evaluation approaches are considered to be inadequate due to the lack of flexibility and an inappropriate structure for addressing the unique organizational demands and contextual factors. To address this challenge effectively, taking a crucial step toward customization of risk evaluation.

In the developing field of nano-materials synthesis, copper oxide nanoparticles (NPs) are deemed to be one of the most significant transition metal oxides because of their intriguing characteristics. Its synthesis employing green chemistry principles has become a key source for next-generation antibiotics attributed to its features such as environmental friendliness, ease of use and affordability. Because they are more environmentally benign, plants have been employed to create metallic NPs. These plant extracts serve as capping, stabilising or hydrolytic agents and enable a regulated synthesis as well.

Organic chemical solvents are harmful and entail intense conditions during nanoparticle synthesis. The copper oxide NPs (CuO-NPs) synthesised by employing the green chemistry principle showed potential antitumor properties. Green synthesised CuO-NPs are regarded to be a strong contender for applications in the pharmacological, biomedical and environmental fields.

The aim of this study is to evaluate the anticancer potential of CuO-NPs plant extracts to isolate and characterise the active anticancer principles as well as to yield more effective, affordable, and safer cancer therapies.

This review article highlights the copper oxide nanoparticle's biomedical applications such as anticancer, antimicrobial, dental and drug delivery properties, future research perspectives and direction are also discussed.

Increasing trends of climatic risk pose challenges to the food security and livelihoods of smallholders in vulnerable regions, where farmers often face loss of the entire crop, pushing farmers (mostly men) out of agriculture in destitution, creating a situation of agricultural making agriculture highly feminization and compelling male farmers to out-migrate. Climate-smart agricultural practices (CSAPs) are promoted to cope with climatic risks. This study aims to assess how knowledge related to CSAPs, male out-migration, education and income contribute to the determinants of male out-migration and CSAPs adoption and how they respond to household food security.

Sex-disaggregated primary data were collected from adopter and non-adopter farm families. STATA 13.1 was used to perform principle component analysis to construct knowledge, yield and income indices.

Yield and income index of adopters was higher for men than women. The probability of out-migration reduced by 21% with adoption of CSAPs. An increase in female literacy by 1 unit reduces log of odds to migrate by 0.37. With every unit increase in knowledge index, increase in log-odds of CSAPs adoption was 1.57. Male:female knowledge gap was less among adopters. Non-adopters tended to reduce food consumption when faced with climatic risks significantly, and the probability of migration increased by 50% with a one-unit fall in the nutrition level, thus compelling women to work more in agriculture. Gender-equitable enhancement of CSAP knowledge is, therefore, key to safeguarding sustainable farming systems and improving livelihoods.

The enhancement of gender equitable knowledge on CSAPs is key to safeguard sustainable farming systems and improved livelihoods.

This study is based on the robust data sets of 100 each of male and female from 100 households (n = 200) using well-designed and validated survey instrument. From 10 randomly selected climate-smart villages in Samastipur and Vaishali districts of Bihar, India, together with focus group discussions, the primary data were collected by interviewing both men and women from the same household.

This study is motivated to provide a theoretically informed, data-driven assessment of the consequences associated with the participation of non-human bots in social accountability movements; specifically, the anti-inequality/anti-corporate #OccupyWallStreet conversation stream on Twitter.

A latent Dirichlet allocation (LDA) topic modeling approach as well as XGBoost machine learning algorithms are applied to a dataset of 9.2 million #OccupyWallStreet tweets in order to analyze not only how the speech patterns of bots differ from other participants but also how bot participation impacts the trajectory of the aggregate social accountability conversation stream. The authors consider two research questions: (1) do bots speak differently than non-bots and (2) does bot participation influence the conversation stream.

The results indicate that bots do speak differently than non-bots and that bots exert both weak form and strong form influence. Bots also steadily become more prevalent. At the same time, the results show that bots also learn from and adapt their speaking patterns to emphasize the topics that are important to non-bots and that non-bots continue to speak about their initial topics.

These findings help improve understanding of the consequences of bot participation within social media-based democratic dialogic processes. The analyses also raise important questions about the increasing importance of apparently nonhuman actors within different spheres of social life.

The current study is the first, to the authors’ knowledge, that uses a theoretically informed Big Data approach to simultaneously consider the micro details and aggregate consequences of bot participation within social media-based dialogic social accountability processes.

This study analyses income inequality and distribution patterns among key actors in the cassava value chain. The study also identifies factors that influence profit of key actors in the cassava value chain.

The study was conducted in Oyo State, Nigeria, using primary data from 620 actors, consisting of 400 farmers, 120 processors and 100 traders in the cassava value chain. The Gini coefficient was used to estimate income inequalities within and between actors. Multiple linear regression was applied to identify factors that influence the profit of the actors in the cassava value chain.

The result shows a gender pattern in the participation in the cassava value chain: men dominate in the production, whereas women mostly engage in processing and marketing of processed cassava products. We also find that incomes are unequally distributed among actors, favouring traders and processors more than farmers in the value chain. Women are better off in processing and trading of value-added products than in the raw cassava production. Spatial differences also contribute to income inequality among farmers in the cassava value chain. An increase in farmers and processors’ incomes reduces inequality in the value chain while an increase in traders’ income widens inequality. Age is significantly negatively correlated with actors’ profit at 1%, while educational level significantly increases their profit at 5%. Processors and traders with large households have a higher profit. We also find that farm size, experience and labour input have significant positive effects on farmers’ profit only at 5%. Membership in an association increases farmers and processors’ profit at 1 and 10%, respectively.

The study recommends that agricultural policies that promote agrifood value chains should aim at minimizing income inequality by targeting vulnerable groups, particularly female farmers to achieve sustainable development in rural communities.

Existing studies recognise income inequality in agricultural value chains in sub-Saharan Africa. However, there are few rigorous quantitative studies that address this pressing issue. Our paper fills this knowledge gap and suggests ways to minimise income inequality in the agri-food value chain, using the example of the cassava value chain in Nigeria.

Effective and flexible organizational models have become an avenue for driving smallholder competitiveness in the agricultural sector. However, little is understood about the processes by which resource-constrained actors deploy their organizational networks to generate and retain value in rapidly changing agrifood environments. This study examines the moderating effects of business contingencies on the interplay between organizational relationships and the resource-based performance of small-scale farmers in a developing country.

The authors propose a novel conceptual framework grounded in the relational view, netchain and contingency theories. Cross-sectional data obtained from 330 maize farmers in rural Zambia were analyzed using variance-based structural equation modeling, which involves mediation-moderation analysis.

The results show that all relational networks – vertical, horizontal and lateral – positively mediate the effects farm resources and social capital have on farmers' performance. However, these effects change depending on the predominant agency situations. Specifically, asymmetric power from customers and reputable competitors weakens the positive effect of closer horizontal relationships on business performance, while the positive effect of tighter informal vertical relationships on farmers' performance weakens under conditions of high affective trust. Moreover, the gender-based multigroup analyses highlight variations in the contingent relational view of men- and women-headed households.

The study relies on cross-sectional data from one agribusiness sector in Zambia, thus generalizations should be cautious.

The uniqueness of this study lies in the proposed theoretical framework and new empirical insights, which extend the scope of the relational view to small-scale farming households in developing countries.

The purpose of this paper is to reveal how support services for open and distance students are designed, developed and implemented to ensure successful learning to take place, with specific references to the Open University of Sri Lanka (OUSL) and Universitas Terbuka (UT) Indonesia. Success in distance learning is one major challenge for open universities to respond to expectations of students and stakeholders. This study focuses on the strategies of student support services in OUSL and UT, investigating related factors including instructional design and development, learning engagement and motivation, policy and strategy in reducing dropouts, use of OER/MOOCs, and quality assurance.

A qualitative study was employed involving analyses of documents; interviews and focus group discussion with senior administrators, academic staff, students; and on-site observation in locations of teaching and learning.

This research is exploratory in nature. Findings of the study are expected to improve our understanding of student support in distance learning, in which analysis is based on good practices, challenges and rooms for improvement of both OUSL and UT.

Findings of this study reveal practices and lessons learnt that may be useful as reference to open universities, taking into considerations the fact that each open university has been established to address specific challenges in its own unique circumstances.

This research may be adopted as baseline framework for analysis of student support for open universities. Further in-depth study is needed to understand how various aspects of student support contribute to success in open and distance learning.

This paper aims to investigate the relationship between general attitude toward advertising and consumers' purchase intention. The relationship between cognitive attitude, intrusiveness attitude, evaluative judgments, affective response and general attitude toward ad was examined. Furthermore, reliability as a moderator in the relationship between cognitive attitude, intrusiveness attitude, evaluative judgments, and affective response and the general attitude toward ad were studied.

Data from women consumers who subscribe to fashion magazines in India were collected and analyzed using a structured survey instrument. Women were selected because the products were related to women, including facial and body-care products, women sportswear, shampoos, lipstick, handbags, etc. Unit of analysis in this research is “observations,” and in all, 400 data points were analyzed, and to test hypothesized relationships, hierarchical regression and logistic regression were employed.

A conceptual model is developed and tested where (1) cognitive attitude toward ad, intrusiveness, evaluative judgments and affective responses are related to general attitude toward ad, and (2) general attitude toward ad is related to purchase intention. The hierarchical regression results show that (1) reliability moderates the relationship between cognitive attitude, intrusiveness, affective responses and general attitude toward ad. The logistic regression results support the positive relationship between general attitude toward ad and purchase intention.

Since the present research is based on self-report measures, the limitations of social desirability bias and common method bias are inherent. Second, this research focuses only on women consumers and products purchased by women. The research has implications for literature on advertising, especially women-related products.

This study contributes to practicing managers who are interested in promoting the women-related products. This study highlights the importance of general attitude toward ad as a precursor for consumers purchase intention. The study provides justification for enormous amounts of money invested in fashion advertising because of their effects on consumer behavior.

This study provides new insights about the effects reliability on general attitude toward ad and consumers' purchase intention. The conceptual model developed in this study adds novelty by considering reliability as a moderator, in addition to the direct relationships which have been studied by earlier researchers.

This study aims to investigate consumer behaviour towards online shopping, which further examines various factors limiting consumers for online shopping behaviour. The purpose of the research was to find out the problems that consumers face during their shopping through online stores.

A quantitative research method was adopted for this research in which a survey was conducted among the users of online shopping sites.

As per the results total six factors came out from the study that restrains consumers to buy from online sites – fear of bank transaction and faith, traditional shopping more convenient than online shopping, reputation and services provided, experience, insecurity and insufficient product information and lack of trust.

This study is beneficial for e-tailers involved in e-commerce activities that may be customer-to-customer or customer-to-the business. Managerial implications are suggested for improving marketing strategies for generating consumer trust in online shopping.

In contrast to previous research, this study aims to focus on identifying those factors that restrict consumers from online shopping.

The paper aims to throw light on the interactions taking place between the different chemical compositions at various temperatures. P-methylacetophenone is a polar dissolvable, which is positively related by dipole–dipole co-operations and is exceptionally compelling a direct result of the shortfall of any critical primary impacts because of the absence of hydrogen bonds; hence, it might work an enormous dipole moment (μ = 3.62 D). Alcohols additionally assume a significant part in industries and research facilities as reagents and pull in incredible consideration as helpful solvents in the green innovation. They are utilized as pressure-driven liquids in drugs, beauty care products, aromas, paints removers, flavors, dye stuffs and as a germ-free specialist.

Mixtures were prepared by mass in airtight ground stopper bottles. The mass measurements were performed on a digital electronic balance (Mettler Toledo AB135, Switzerland) with an uncertainty of ±0.0001 g. The uncertainty in mole fraction was thus estimated to be less than ±0.0001. The densities of pure liquids and their mixtures were determined using a density meter (DDH-2911, Rudolph Research Analytical). The instrument was calibrated frequently using deionized doubly distilled water and dry air. The estimated uncertainty associated with density measurements is ±0.0003 g.cm⁻³. Viscosities of the pure liquids and their mixtures were determined by using Ostwald’s viscometer. The viscometer was calibrated at each required temperature using doubly distilled water. The viscometer was cleaned, dried and is filled with the sample liquid in a bulb having capacity of 10 ml. The viscometer was then kept in a transparent walled water bath with a thermal stability of ±0.01K for about 20 min to obtain thermal equilibrium. An electronic digital stop watch with an uncertainty of ±0.01 s was used for the flow time measurements for each sample at least four readings were taken and then the average of these was taken.

Negative values of excess molar volume, excess isentropic compressibility and positive values of deviation in viscosity including excess Gibbs energy of activation of viscous flow at different temperatures (303.15, 308.15 and 313.15 K) may be attribution to the specific intermolecular interactions through the hetero-association interaction between the components of the mixtures, resulting in the formation of associated complexes through hydrogen bond interactions.

The excess molar volume (V^E) values were analyzed with the Prigogine–Flory–Patterson theory, which demonstrated that the free volume contribution is the one of the factors influencing negative values of excess molar quantities. The Jouyban–Acree model was used to correlate the experimental values of density, speed of sound and viscosity.