Search results

Exposure to unhealthy lifestyle behaviours before pregnancy affects the health of mothers and their (unborn) children. A social marketing strategy could empower prospective parents to actively prepare for pregnancy through preconception care (PCC). This study aims to describe the development of a PCC social marketing strategy based on the eight-point benchmark criteria for effective social marketing and to clarify the concept of using social marketing for health promotion purposes.

An extensive literature search was carried out regarding the needs of the target population and PCC behavioural goals, leading to the development of a bottom-up, ambassador-driven, communication concept.

In-depth insights of all benchmarks were analysed and incorporated during the development process of a new PCC social marketing strategy, with a special focus on the application of the “Health Belief Model” (Benchmark 3) and “the Four-P framework” (Benchmark 8). Evidence-based preconceptional health information is our product, for a low price as the information is freely attainable, promoting a message of overall women‘s health and online or through a consult with a health-care provider as the appropriate place. This formative research resulted in the development of the Woke Women® strategy, empowering women to actively prepare for pregnancy.

Developing a social marketing strategy to enhance actively preparing for pregnancy shows potential to encourage prospective parents to adopt healthier preconceptional lifestyle behaviours and can therefore improve the health of future generations.

Using overlapped portfolio data on public equity funds in Korea, the authors construct several types of fund-stock weighted bipartite networks and measure fund network centrality. The authors also examine the relationship between network centrality and fund investment performance. The authors' results are three-fold. First, the authors find that the fund centrality of the network in which funds and stocks are connected based on the most active investing behavior positively affects the fund performance. Second, the funds with a high centrality level based on the same network generate higher returns by holding stocks with high value uncertainty. Third, the authors find that fund centrality is not associated with herd behavior. Based on these results, the authors argue that fund centrality is a proxy of information advantage and skill of fund managers. The authors' paper shows that network analysis could be a new way to identify funds with better performance and measure the skill and information advantage to construct an optimal portfolio.

In this research, the authors demonstrate the advantage of reinforcement learning (RL) based intrusion detection systems (IDS) to solve very complex problems (e.g. selecting input features, considering scarce resources and constrains) that cannot be solved by classical machine learning. The authors include a comparative study to build intrusion detection based on statistical machine learning and representational learning, using knowledge discovery in databases (KDD) Cup99 and Installation Support Center of Expertise (ISCX) 2012.

The methodology applies a data analytics approach, consisting of data exploration and machine learning model training and evaluation. To build a network-based intrusion detection system, the authors apply dueling double deep Q-networks architecture enabled with costly features, k-nearest neighbors (K-NN), support-vector machines (SVM) and convolution neural networks (CNN).

Machine learning-based intrusion detection are trained on historical datasets which lead to model drift and lack of generalization whereas RL is trained with data collected through interactions. RL is bound to learn from its interactions with a stochastic environment in the absence of a training dataset whereas supervised learning simply learns from collected data and require less computational resources.

All machine learning models have achieved high accuracy values and performance. One potential reason is that both datasets are simulated, and not realistic. It was not clear whether a validation was ever performed to show that data were collected from real network traffics.

The study provides guidelines to implement IDS with classical supervised learning, deep learning and RL.

The research applied the dueling double deep Q-networks architecture enabled with costly features to build network-based intrusion detection from network traffics. This research presents a comparative study of reinforcement-based instruction detection with counterparts built with statistical and representational machine learning.

This paper aims to construct a process model of business founding in the biotech industry.

An inductive method is used, and five case studies analyzed. Data are coded by applying Gioia’s method.

Aspirant entrepreneurs conduct resource analysis and industry analysis to formulate research and development targets. They perform transactions and networks because they require resources, and they then deploy and coordinate these resources. Such coordination generates activities with social and financial impacts.

The results are specific to the biotech industry. A future study could examine business founding processes in other industries (e.g. entertainment, fashion, public utilities and sport). Additionally, the paper argues that during the founding process entrepreneurs show little concern for knowledge-sharing risk, as they want to collaborate to implement their ideas. Quantitative papers could test the consequences of such behavior.

The process model provides insights into aspirant founders on how to start a business in the biotech industry.

The paper shows: the differences between the founding process in the biotech industry versus other industries; and the shape of the Bower–Burgelman model in the context of biotech business founding. The paper delineates how private companies discover competencies in the public sector; a model of technology transfer from public to private sector; entrepreneurs’ absence of risk perceptions regarding knowledge-sharing during founding; and how conferences can serve as vehicles for benchmarking in networking.

One key determinant of entrepreneurial success is entrepreneurial self-efficacy (ESE), defined as an individual’s confidence in his or her ability to perform entrepreneurial tasks. Whereas previous research has examined how individual and business factors influence ESE, the purpose of this paper is to analyze the influence of entrepreneurs’ social networks upon ESE. The paper examines such relationships for black and white entrepreneurs.

In total, 110 black and white entrepreneurs responded to a survey measuring ESE and critical constructs representing elements of the quality of entrepreneurs’ networks: emotional carrying capacity (ECC) and network ethnic diversity.

The authors found significant, positive relationships between both ECC and network ethnic diversity on ESE for white entrepreneurs but only found a significant positive relationship between ECC and ESE for black entrepreneurs.

While research is clear about the role that ESE plays in entrepreneurial activities, few studies have focused on the factors that improve ESE. In the present work, the authors study the role of context by examining how entrepreneurs’ social networks influence ESE. The authors examine such influences for both white and black entrepreneurs to better understand the implications of ethnicity.

Social innovation is a recent theme, and the practices related to this area are characterized by punctual actions and projects restricted by time and space that make it difficult to develop strategies that can be sustained in this field. Therefore, one point that deserves to be highlighted in studies on social innovation is a matter of scalability. This paper aims to deal with a bibliometry whose objective was to map the existing studies about scalability of social innovation carried out in the Capes and EBSCOHost portals.

This paper deals with a bibliometry. The topic researched in this bibliometry is scalability of social innovation. The databases chosen for this research were Portal Periódico Capes and EBSCOHost because they are the leading providers of search databases.

A total of 42 papers were considered, distributed between 2002 and 2017. The analysis criteria for the study were origin (composed by year, author, country of origin, periodical and impact factor), focus of the investigations, justification, method and main techniques of research, contributions and theoretical advances and challenges and paths.

Among the main results found, one of them is that scalability is a topic that began to be researched recently, so that the USA and Brazil lead the research. Most of the studies focused on the scalability process and justified the importance of studies on the subject as a way to explore the potential of expanding the social impacts of a social innovation. Several studies have emphasized the role of networks as being quite positive for the scalability process and have been concerned with identifying factors that contribute to the scalability process. The challenge that most stood out among the papers was the financial sustainability of a social innovation. At the end, a research agenda was proposed.

The purpose of this paper is to review the current literature in the field of tourism demand forecasting.

Published papers in the high quality journals are studied and categorized based their used forecasting method.

There is no forecasting method which can develop the best forecasts for all of the problems. Combined forecasting methods are providing better forecasts in comparison to the traditional forecasting methods.

This paper reviews the available literature from 2007 to 2017. There is not such a review available in the literature.

The aim of this chapter is to describe a four-type model of organisational structures and to discuss two cases, Embrapa and the Brazilian Agricultural Research Corporation, as well as additional cases at SAM-Research and the centre for shared medical support services established at the University of Bologna.

These cases should help readers understand the importance of designing distinctive, tailored-made support services while keeping these structures flexible for further adaptation under unforeseen changes.

The chapter concludes by stressing the role of institutions to steadily invest in the design of these tailored support structures and in personalised training for their support staff.

This study investigates how asset specificity, relational governance and firm adaptability relate with supply chain integration (SCI), considering selected food processing firms (FPFs) in Uganda.

This study applies a quantitative research methodology. This research draws on a sample of 103 FPFs that have been selected from a population of 345 FPFs located in Kampala district. Hypothesis testing was done using Smart PLS version 3.

Asset specificity has a significant positive relationship with SCI, and firm adaptability partially mediates this relationship. Also, there is a full mediation impact of firm adaptability on the relationship between relational governance and SCI.

This study focused on perceptual measures to get responses from managers on the level of integration with key suppliers and customers, yet firms deal with a number of suppliers and customers.

This study contributes to existing literature on SCI by applying the transaction cost theory. The study focuses on the influence of asset specificity, relational governance and firm adaptability on SCI in the food processing sector. Literature on relational governance in supply chain using the transaction cost theory remains scanty. Few studies have also focused on firm adaptability as a mediator in the FPS with specific focus on Uganda, yet the sector is highly faced with uncertain events. The uncertain events in the sector and in developing countries call for adaptive strategies. Additionally, this study is the first to use firm adaptability to mediate the influence of asset specificity and relational governance on SCI more so in a developing country like Uganda where the FPS is one of the most important in the economy.

The purpose of the study is to perform a scientific mapping and detect the evolution pattern of two emerging fields, organizational capabilities and sustainable supply chain management (SSCM), to detect and visualize the existing conceptual domains and identify less-explored areas.

This study uses a methodological combination involving systematic literature review and bibliometric analysis. The methodology was implemented in the following order: definition and selection of the material using an electronic database, descriptive analysis of the material, category selection using bibliographic coupling analysis by VOSviewer (clusterization), material evaluation and content analysis.

The research results clarify the intellectual structure within the academic field. The authors’ identified three main clusters: (1) sustainable capabilities and practices in supply chain management (SCM), (2) green SCM and performance and (3) information technology and innovation. The findings reveal that there is a rich field to be explored, especially regarding issues involving sustainable technological capabilities, sustainable initiatives and key resource development.

This study facilitates researchers’ and practitioners’ understanding and their ability to map the different paths and evolution of SSCM and organizational capabilities. It can encourage managers and policymakers alike to conceive new approaches to engage in the adoption of SSCM.

This work employs a singular approach to identify the intellectual knowledge and topics related to the implementation of SSCM by adopting the theoretical approach of sustainable organizational capacity. It contributes to the debate on distinguishing specific sustainable organizational capabilities from traditional capabilities.