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Based on farm diversification's conventional and unconventional nature, the study intends to discriminate different profiles of farm diversification businesses. Furthermore, this study analyses the links between farm diversification efforts, (open) innovation networks as well as the environmental performance (EP) and financial performance (FP) of farms.

A questionnaire was administered through personal interviews with 160 fresh fruit farmers in an inland Portuguese region. Linear regression, latent class analysis (LCA) and multinomial logistic regression were used.

There are significant differences between the levels of diversification, performance and participation in (open) innovation networks of the three classes of farmers discriminated. Different types of diversification efforts and (open) innovation networks influence EP and FP, while FP and R&D projects are associated with the likelihood of being part of a farm diversification class. Moreover, this study shows that innovation networks, promoted by specialized agricultural advisors and R&D projects, are important forms of open innovation in the agricultural sector.

The study contributes to understanding the agricultural sector's diversification efforts and (open) innovation networks and their association with EP and FP. The conventional or unconventional nature of farm diversification was self-reported.

European and local institutions are advised to develop more R&D programs directed to farmers, including environmental and financial issues, besides comprising agricultural and non-agricultural diversification.

This study provides new insights to understand the association between diversification efforts, (open) innovation networks and agricultural businesses' performance.

This study proposes a new method to investigate adoption of new technologies and tests this method by looking into the determinants of internet banking adoption in Brazil.

A total of 600 respondents living in one of the biggest cities in Brazil were sampled for interviewing: 300 were internet bank users, 150 were internet but not internet bank users, and 150 were neither internet nor internet bank users.

The adjusted coefficient of determination in the multiple linear regression equation (dependent variable: intention to use/continue to use IB) was 60 percent and the main effects of the eight variables proved significant (relative advantage of control, compatibility with lifestyle, image, subjective norm, self‐efficacy, relative advantage of security and privacy, results demonstrability, and trialability). The McFaden pseudo coefficient of determination in the multinomial logistic regression equation (dependent variable: a dummy variable for each of the three groups analyzed) ranged from 45 percent to 69 percent. The findings show that the variables that influence the intention to use/continue to use IB are not exactly the same as those that influence actual adoption. Specifically, the results seem to suggest that intention to use IB is influenced solely by people's beliefs about IB, while its actual adoption is influenced also by individual characteristics.

The findings herein suggest that the proposed integrated model offers superior ability to explain adoption of internet banking to that of the models elected by previous studies. Furthermore, the model looks not only into the intentions but also into actual adoption.

Introduction. This study examined the association between self-rated physical and oral health, cigarette smoking, and history of criminal justice contact (i.e., never arrested; arrested, but never incarcerated; or incarcerated in reform school, detention, jail, or prison) among African American men and women. Methods. We conducted descriptive statistical, linear regression, and multinomial regression analyses of the African American subsample (n = 3,570) from the National Survey of American Life (2001–2003). Results. Overall, African American women reported lower arrest rates and histories of incarceration than African American men. Additionally, we found that criminal justice contact was associated with lower self-rated physical health and oral health and higher levels of smoking for both men and women. African American women who had been arrested and detained in facilities other than jail had more chronic health problems than their male counterparts. Furthermore, having been arrested or spent time in a reform school, detention center, jail, or prison significantly increased the odds of African American men being a current smoker. Lastly, among African American women, those who had any level of criminal justice contact were likely to be current smokers and former smokers compared to those without a history of criminal justice contact. Conclusion. Addressing the health of African Americans with criminal justice contact is a critical step in reducing health disparities and improving the overall health and well-being of African American men and women. Furthermore, attention to differences by gender and specific types of criminal justice contact are important for a more precise understanding of these relationships.

India is facing a double burden of malnutrition, i.e. undernutrition and obesity. Women and adolescent health and nutrition are very relevant issues which have not received much attention it deserves in India, especially in the context of a girl child. Hence, the purpose of this study is to assess malnutrition among women and adolescent girls as well as the associated factors.

An attempt was made to assess malnutrition among women and adolescent girls and associated factors. The required data was collected from the north (616) and south transects (659) sample households of Bangalore constituting a total sample size of 1,275. The data was analyzed by adopting multiple linear regression and multinomial logistic regression analysis using STATA software.

The effects of this study simply confirmed that, urbanization had an instantaneous effect on dietary repute of women and adolescent girls, while transferring throughout the gradient from rural to urban with the growing significance of weight problems and obese. In adolescent girls, about 31% were underweight followed by normal weight and overweight across rural–urban interface of Bangalore. The factors such as education, consumption of meat and animal products, a dummy for urban, diabetes and blood pressure were significantly and positively influencing the nutritional status (Body Mass Index) of women across rural–urban interface. While consumption of vegetables, wealth index and per capita income had a positive and significant influence on the nutritional status of adolescent girls.

With limited studies and data available in Karnataka, especially in Bengaluru, one of the fastest growing cities in the world. Against this backdrop, the study was conducted to assess the prevalence of malnutrition among women and adolescents and its association with various socio-economic variables.

Though different claims are made in the literature with regard to learning approach differences between mature and non-mature university students, the issue seems to bare detailed study. The purpose of this paper is to report about an investigation of mature and non-mature university students’ learning strategies. The authors examine the relationship between age and learning strategy, and assess to what extent this relationship is mediated by individual and contextual factors.

Using original survey data on 448 university students enroled in Social Sciences programmes in Belgium, this paper examines the relationship between age and learning strategy and assesses to what extent this relationship is mediated by individual and contextual factors.

The results of the multinomial logistic regression show significant differences in learning strategies between both groups of learners. The analyses suggest that mature students are 15.3 percentage points more likely than regular students to adopt a navigator learning strategy. The navigator strategy develops in a non-linear way between the ages 30 and 37. Moreover, only a small part of the learning strategies of mature learners can be explained by mediating factors, with the job involvement playing a particular role.

This study contributes to the body of knowledge concerning the assessment and classification of learning strategies, including a focus on mediators affecting such strategies. The results are confined to only two higher education (HE) institutions. Furthermore, there may be a non-response bias; it is plausible that we miss among the respondents a particular type of mature students such as those that do not like to participate or those that have dropped out of their master’s programme. By means of larger, random samples in future research we should verify this study’s conclusions. This study did not include motivation as a variable. However, it might also explain why mature and non-mature students’ learning approaches differ. Further research could entangle motivational components in relation to learners’ studying approaches.

The research results contribute to our understanding to what extent mature and non-mature students’ learning strategies differ and which mediators are prevalent in explaining these differences. It helps to understand how universities can create a supportive academic environment for mature learners.

The authors found significant differences with regard to learning strategies between mature and non-mature university students. Furthermore, having a professional occupation plays a mediating role in explaining learning strategy differences. The study raises the issue of learner-centred HE, with considerations about differentiated designs of learning environments, programmes and support services targeting students of different ages. By integrating the Assessing the Learning Strategies of Adults instrument, instructional designers can identify learning strategies and take appropriate action to accommodate learners. Additionally, awareness of one’s own learning strategy strengthens mature students’ decision making in self-directed learning environments. In that respect, the authors note also that higher pedagogical flexibility, i.e. more varied educational formats, tracks and study arrangements, ensures adult learners’ access, persistence and retention in HE.

Previous studies suggest that student learning approaches are distinguishable, but did not yet focus on differences between non-mature and mature students. As the authors include graduate students in this study, the focus is on a group which has not been studied previously.

Past marketing research has found that hedonic utility is more important for Western cultures, whereas social utility is more important for Eastern cultures, suggesting differential positioning in each culture. However, the research has so far focused on a single choice context of one brand. This paper aims to examine cultural differences in utility importance using two brand choice contexts: single choice and brand selection.

Four studies (n = 1268) were conducted. Study 1 focused on a single choice context by asking directly about utility importance when choosing a cellphone. Study 2 focused on a brand selection context using conjoint analysis for the same cellphone category used in Study 1. To validate the results of Studies 1 and 2 with the categories of perfume, sports shoes and computers, Study 3 analyzed single and selection contexts using latent regression methods. Finally, Study 4 explored the role of cognitive load in explaining the differences between the two choice contexts using the laptop category.

The analyses of the brand selection context, which simulates real-life choice, revealed that the importance ascribed to utilities was not idiosyncratic for each culture. In contrast, single-choice contexts demonstrated stereotypical cultural differences.

Positioning a specific utility message to fit the culture stereotype might not be necessary, as it does not always affect brand choice in a competitive environment.

Many companies lack insights or fact-based support for the pricing decisions they make in an increasingly complex environment. In order to optimize their pricing process, managers need to identify key indicators that may influence the performance of their decisions. The purpose of this paper is to report an investigation of pricing determinants in large companies manufacturing capital goods in France. First a conceptual framework is proposed, in order to fill several gaps identified in the literature on pricing practices and more precisely by operating a distinction between environmental variables (determinants), decision making (pricing strategy and price and product-line structures) and its consequence in terms of price level.

The author conducted an empirical research on the determinants of the pricing process. This study consistedof a questionnaire survey addressed to pricing managers (or executives in charge of pricing) in 98 of the largest manufacturing companies in France about their new-product pricing decision-making process.

The author studies environmental determinants and their influence on the pricing and describes the structure of pricing determinants as a five dimensions construct: market-based, value-based, position-based, competition-based and production-based. The results show that firms rely on environmental determinants as indicators of their pricing flexibility. These indicators operate as pricing levers: a good position on these variables gives firms more pricing power. But in the vast majority of the cases, companies extensively relied on competitive conditions instead of taking advantage of a favorable position, described as pricing myopia.

This paper describes current pricing practices in leading companies with key informants (mainly pricing managers) highly involved in the pricing decision process, and contrasts two pricing orientations, pricing power vs pricing myopia.

This paper examines differences in the discounts offered during Deal of the Day (DOD) promotion schemes by online retailers based on product category, festival season and the economic status of a country.

In study 1, the authors conducted three focus group studies and 20 in-depth personal interviews (PIs) to explore consumers' perspectives on DOD. To validate the hypotheses based on the findings of study 1 and collected 515 data points from Amazon.com (313 data points from the United States) and Amazon.in (202 data points from India) in study two. The authors used multinomial linear regression to analyze the data.

A significant difference in savings for buyers on the purchase of electronic product categories as compared to savings made by them on the purchase of non-electronic product categories during DOD promotional schemes. Electronic products get deeper discounts in the US during festival seasons as compared to non-festival seasons during DOD promotional schemes. In emerging economies discounts offered by e-commerce retailers during DOD offers on electronic items are lesser as compared to those offered during DOD offers made in developed economies like United States.

Managers should avoid offering the same products under DOD during the festive season and non-festive season at similar prices in emerging economies as during festivals customers expect more savings over and above the regular savings.

DOD is offered every day irrespective of the other promotions on e-commerce platforms to boost sales. This study analyses any significant difference in saving for DOD offered during special sales days in emerging and developed economies.

Most literature on ambidexterity has focused on large firms and on the influence of internal issues in this strategy, that is, organizational structures, top management integration, or internal knowledge management processes (Lutbatkin et al., 2006; Chang et al., 2011; Lee and Huang, 2012). The purpose of this paper is to assess small- to medium-sized enterprises (SMEs)’ ambidexterity strategies during economic recession periods in comparison with those of large firms and identify the managerial external capabilities which are associated with the development of SMEs’ ambidexterity.

A multinomial logit model and a probit model are proposed and tested using data collected from 2,150 Spanish firms during the period of 2009-2013.

The data analysis reveals that SMEs develop more ambidextrous innovation strategies in recession periods than larger firms do. Moreover, two managerial external capabilities have been identified as drivers of SMEs’ ambidextrous behavior in crisis periods: first, the capability of top management to anticipate scenarios; and second, the capacity to acquire adequate external resources through co-operation.

The results show that SME managers wanting to develop ambidextrous strategies in recession periods have to forecast scenarios in terms of innovation difficulties and strengthen their resources through co-operation. Implementation of public policy is encouraged to support these capabilities, thus enhancing SME sustainability in uncertain contexts.

Prior studies have paid little attention to the role of external capabilities. Although their role was revealed as a relevant dimension in the study of SME ambidexterity in adverse contexts by Cao et al. (2010), it remained underexplored. This paper aims to fill this gap.

Purchase conversion prediction aims to improve user experience and convert visitors into real buyers to drive sales of firms; however, the total conversion rate is low, especially for e-retailers. To date, little is known about how e-retailers can scientifically detect users' intents within a purchase conversion funnel during their ongoing sessions and strategically optimize real-time marketing tactics corresponding to dynamic intent states. This study mainly aims to detect a real-time state of the conversion funnel based on graph theory, which refers to a five-class classification problem in the overt real-time choice decisions (RTCDs)—click, tag-to-wishlist, add-to-cart, remove-from-cart and purchase—during an ongoing session.

The authors propose a novel graph-theoretic framework to detect different states of the conversion funnel by identifying a user's unobserved mindset revealed from their navigation process graph, namely clickstream graph. First, the raw clickstream data are identified into individual sessions based on a 30-min time-out heuristic approach. Then, the authors convert each session into a sequence of temporal item-level clickstream graphs and conduct a temporal graph feature engineering according to the basic, single-, dyadic- and triadic-node and global characteristics. Furthermore, the synthetic minority oversampling technique is adopted to address with the problem of classifying imbalanced data. Finally, the authors train and test the proposed approach with several popular artificial intelligence algorithms.

The graph-theoretic approach validates that users' latent intent states within the conversion funnel can be interpreted as time-varying natures of their online graph footprints. In particular, the experimental results indicate that the graph-theoretic feature-oriented models achieve a substantial improvement of over 27% in line with the macro-average and micro-average area under the precision-recall curve, as compared to the conventional ones. In addition, the top five informative graph features for RTCDs are found to be Transitivity, Edge, Node, Degree and Reciprocity. In view of interpretability, the basic, single-, dyadic- and triadic-node and global characteristics of clickstream graphs have their specific advantages.

The findings suggest that the temporal graph-theoretic approach can form an efficient and powerful AI-based real-time intent detecting decision-support system. Different levels of graph features have their specific interpretability on RTCDs from the perspectives of consumer behavior and psychology, which provides a theoretical basis for the design of computer information systems and the optimization of the ongoing session intervention or recommendation in e-commerce.

To the best of the authors' knowledge, this is the first study to apply clickstream graphs and real-time decision choices in conversion prediction and detection. Most studies have only meditated on a binary classification problem, while this study applies a graph-theoretic approach in a five-class classification problem. In addition, this study constructs temporal item-level graphs to represent the original structure of clickstream session data based on graph theory. The time-varying characteristics of the proposed approach enhance the performance of purchase conversion detection during an ongoing session.