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This paper presents the particle swarm optimization (PSO) algorithm in conjuction with the fuzzy logic method in order to achieve an optimized tuning of a proportional integral derivative controller (PID) in the DTC control loops of dual star induction motor (DSIM). The fuzzy controller is insensitive to parametric variations, however, with the PSO-based optimization approach we obtain a judicious choice of the gains to make the system more robust. According to Matlab simulation, the results demonstrate that the hybrid DTC of DSIM improves the speed loop response, ensures the system stability, reduces the steady state error and enhances the rising time. Moreover, with this controller, the disturbances do not affect the motor performances.

The paper has a twofold purpose: (1) to test the application of means-end theory to providers of hospitality goods and services, and (2) to explore this question in the context of winery tasting rooms when they had a unique opportunity to restructure their hospitality experience due to government restrictions in response to COVID.

A qualitative approach was adopted, and a convenience sample was used to conduct semi-structured laddering interviews. Forty interview transcripts were coded as means-end ladders, which were analyzed using a custom computer program to develop the implication matrix and the hierarchical value map.

This paper demonstrates that means-end is a useful approach to investigate the values and behaviors of the producer, specifically hospitality hosts. It finds that the principal goal of tasting rooms is to generate sales, and offering a compelling guest experience is the characteristic that contributes the most to achieving that goal. The staff and the atmosphere created for the guests are the two factors with the greatest influence on the guest experience.

This is the first paper to use means-end theory to study the hospitality host, or the producer of goods and services in general, and the first to study winery hospitality primarily through the lens of means-end theory. The study also helps fill a gap in research on tasting room sales focused on the winery’s goals.

This chapter examines representations of gender in online modafinil markets. While gender has often been absent from scholarship on online drug markets, our analysis demonstrates the ubiquity of gender in representations of modafinil users and sellers. The analysis draws on visual images, blogs, and marketing emails relating to three websites selling modafinil, discussed pseudonymously. We describe the range of ways that notions of gender are represented in advertising. Although women represent around 40% of that buying modafinil online, websites and communications tended not to feature women. Although sexist stereotypes of women were rarely present (in contrast to direct-to-consumer pharmaceutical advertising), the ways that modafinil was imagined tended to focus narrowly on corporate spheres of work and productivity. We contrast this narrow imaginary with female journalists’ own accounts of using modafinil to manage illness and enhance creativity. Thus, we conclude that the ways that modafinil has been imagined reflects working assumptions as to who is considered the ‘normal’ participant in online modafinil markets.

This teaching case aims to analyze the business model of Amaro, a company that directly sells lifestyle goods to end consumers (B2C), focused on the women's market. Amaro's original business model is introduced and a challenging dilemma is proposed: could Amaro innovate its business model, moving from a digitally native vertical brand (DNVB)-type company to a platform, specifically a vertical marketplace focused on the female audience? Would Amaro be prepared for this evolution or would it be more appropriate to focus on or strengthen the DNVB model?

This teaching case was developed based on in-depth interviews with Amaro's leadership. The teaching notes were proposed based on business model innovation, competitive positioning and market trends concepts. The teaching case considers a new type of business model called DNVB. Students can review the concepts, create analyses and recommend which strategic options can leverage the company for a new growing cycle.

Using the case study in the classroom should promote the discussion and reflections on business model innovation and the future of retail in omnichannel contexts - Amaro offers products online (on an e-commerce platform and native mobile applications) and physically in locations called guide shops. The authors suggested the adoption of frameworks and tools (e.g. the competitive positioning map to allow students to visualize ways to compare strategies and make decisions).

The case introduces a fictional dilemma related to the decision to maximize offline or online investments or completely change the company's business model by adding a new vertical marketplace approach.

This teaching case contributes to the student's learning about business model innovation and evolution. Case discussions could explore contemporary concepts such as value proposition, disintermediation and omnichannel commerce.

Offering goods directly to the consumers by using modern technological architecture through vertical integration within the supply chain makes the DNVB business model an original topic in the start-up segment.

Cyber resilience has emerged as an approach for seaports to deal with cyberattacks; it emphasizes ports’ ability to prepare for an attack and to keep operating and recover quickly. However, little research has been undertaken on the challenges of governing cyber risks in seaports. This study aims to address this gap.

Governing cyber resilience is shaped by distributed responsibilities, uncertainties and ambiguities. The authors use this conceptualization to explore the governance of cyber risks in seaports, taking the Port of Rotterdam as a case study and analyzing semistructured interviews with stakeholders, participatory observation and policy documents and legislation.

The authors found that many strategies for governing cyber risks remain dedicated to protecting computer systems against cyberattacks. Nevertheless, port stakeholders have also developed strategies in anticipation of disruptions. However, these strategies appear informal and uncoordinated due to a lack of information exchange, insufficient knowledge regarding cyber risks and disagreement about how to make the Port of Rotterdam cyber resilient. What mainly hampers the cyber resilience of the port is the lack of a comprehensive regulatory framework and economic incentives. The authors conclude that resilience is merely an ideal at the Port of Rotterdam, meaning related governance strategies remain incremental and await institutionalization.

This paper offers insights into the cyber resilience of critical socio-technical systems, which have been underexposed in cyber resilience debates, but, when exploited, can manifest in large-scale disruptions.

Supporting distant teams is a frequent phenomenon. Through the lens of the social identity theory, this research aims to examine differences between local and distant fans regarding drivers of team identification.

A multigroup structural equation model was employed. The data were collected through an online survey with 1,285 sports fans.

Team distinctiveness constitutes an important aspect fueling identification for all fans, whereas congruence between own and team personality is important for local and displaced fans only. Team prestige does not impact identification for either group.

To build up a base of highly identified supporters, clubs should emphasize those aspects of team brands that fans consider distinctive. When targeting local fans, clubs should also focus on communicating the brand's unique personality aspects.

This is the first study that assesses the potential differences behind fans' social identification with local and distant teams.

Prediction is a critical task in targeted online advertising, where predictions better than random guessing can translate to real economic return. This study aims to use machine learning (ML) methods to identify individuals who respond well to certain linguistic styles/persuasion techniques based on Aristotle’s means of persuasion, rhetorical devices, cognitive theories and Cialdini’s principles, given their psychometric profile.

A total of 1,022 individuals took part in the survey; participants were asked to fill out the ten item personality measure questionnaire to capture personality traits and the dysfunctional attitude scale (DAS) to measure dysfunctional beliefs and cognitive vulnerabilities. ML classification models using participant profiling information as input were developed to predict the extent to which an individual was influenced by statements that contained different linguistic styles/persuasion techniques. Several ML algorithms were used including support vector machine, LightGBM and Auto-Sklearn to predict the effect of each technique given each individual’s profile (personality, belief system and demographic data).

The findings highlight the importance of incorporating emotion-based variables as model input in predicting the influence of textual statements with embedded persuasion techniques. Across all investigated models, the influence effect could be predicted with an accuracy ranging 53%–70%, indicating the importance of testing multiple ML algorithms in the development of a persuasive communication (PC) system. The classification ability of models was highest when predicting the response to statements using rhetorical devices and flattery persuasion techniques. Contrastingly, techniques such as authority or social proof were less predictable. Adding DAS scale features improved model performance, suggesting they may be important in modelling persuasion.

In this study, the survey was limited to English-speaking countries and largely Western society values. More work is needed to ascertain the efficacy of models for other populations, cultures and languages. Most PC efforts are targeted at groups such as users, clients, shoppers and voters with this study in the communication context of education – further research is required to explore the capability of predictive ML models in other contexts. Finally, long self-reported psychological questionnaires may not be suitable for real-world deployment and could be subject to bias, thus a simpler method needs to be devised to gather user profile data such as using a subset of the most predictive features.

The findings of this study indicate that leveraging richer profiling data in conjunction with ML approaches may assist in the development of enhanced persuasive systems. There are many applications such as online apps, digital advertising, recommendation systems, chatbots and e-commerce platforms which can benefit from integrating persuasion communication systems that tailor messaging to the individual – potentially translating into higher economic returns.

This study integrates sets of features that have heretofore not been used together in developing ML-based predictive models of PC. DAS scale data, which relate to dysfunctional beliefs and cognitive vulnerabilities, were assessed for their importance in identifying effective persuasion techniques. Additionally, the work compares a range of persuasion techniques that thus far have only been studied separately. This study also demonstrates the application of various ML methods in predicting the influence of linguistic styles/persuasion techniques within textual statements and show that a robust methodology comparing a range of ML algorithms is important in the discovery of a performant model.

Seaports play an immeasurable role in the advancement of international trade. They have been the common avenue for the transportation of goods and services from one continent to another, and it has also been the linking transport of one mode of transport to another. The study sought to assess the effect of paperless information technology (IT)-based custom clearance at Ghana Seaports on businesses and industrial supply chains in Ghana.

The study conducted a survey with a sample size of 200 trading firms in Ghana.

The study discovered that IT-based port clearance has positive impact on customer order fulfillment, transaction cost reduction and supply chain relationships.

With the aim of making Ghana the transportation hub of businesses in the sub region, the paperless custom clearance has the potential to reduce delays at the port and improve their supply chain.

This paper provides researchers with a contemporary perspective toward understanding the effect of paperless custom clearance on the supply chain of businesses in the West African sub region.

Household food insecurity and poor well-being have increased during the coronavirus disease 2019 (COVID-19) pandemic and resulting lockdown measures. Home food growing has been associated with improved food access and well-being, but it is unknown what role it plays during food supply crises and lockdown. It is also unclear how home food growing and social restrictions may affect opinions about growing food in urban areas (i.e. urban agriculture; UA).

A cross-sectional online survey was conducted during the UK national lockdown in March-April 2020 to measure home food growing, perceived food insecurity, well-being, and opinions of UA. The participants were 477 UK-based adults (369 female, mean age 39.57 years ± 13.36); 152 participants were engaged in home food growing prior to the pandemic. Responses were compared to data collected from a separate sample of participants before the pandemic (N=583) to explore potential shifts in opinions about UA.

Participants who engaged in home food growing had lower levels of food insecurity (U_­=19894.50, z=−3.649, p<0.001, r=−0.167) and higher well-being (U=19566.50, z=−3.666, p<0.001, r=−0.168) than those not engaged in home food growing. Perceived food insecurity partially mediated the relationship between home food growing and well-being; home food growing was associated with less food insecurity, which in turn was associated with better well-being. There were no differences in opinions of UA compared to the sample of participants from before the pandemic.

Home food growing may have had a protective effect over perceived food security and well-being in the early stages the pandemic. Opinions of UA were positive and unchanged compared to data collected pre-pandemic. Policies that support home food growing and access to suitable growing spaces and resources may be beneficial for food system resilience and well-being.