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The purpose of this paper is to try to reach the main factors that could put national security at risk as a result of government cloud computing programs.

The paper adopts the analytical approach to first lay foundations of the relation between national security, cybersecurity and cloud computing, then it moves to analyze the main vulnerabilities that could affect national security in cases of government cloud computing usage.

The paper reached several findings such as the relation between cybersecurity and national security as well as a group of factors that may affect national security when governments shift to cloud computing mainly pertaining to storing data over the internet, the involvement of a third party, the lack of clear regulatory frameworks inside and between countries.

Governments are continuously working on developing their digital capacities to meet citizens’ demands. One of the most trending technologies adopted by governments is “cloud computing”, because of the tremendous advantages that the technology provides; such as huge cost-cutting, huge storage and computing capabilities. However, shifting to cloud computing raises a lot of security concerns.

The value of the paper resides in the novelty of the topic, which is a new contribution to the theoretical literature on relations between new technologies and national security. It is empirically important as well to help governments stay safe while enjoying the advantages of cloud computing.

Regulatory initiatives and related technological shifts have been imposing restrictions on data-driven marketing (DDM) practices. This paper aims to find the main restrictions for DDM and the key management theories applied to investigate the consequences of these restrictions.

The authors conducted a unified bibliometric analysis with 104 publications retrieved from both Scopus and Web of Science, followed by a qualitative, in-depth systematic literature review to identify the management theories in literature and inform a research agenda.

The fragmentation of the research outcomes was overcome by the identification of 3 main clusters and 11 management theories that structured 18 questions for future research.

To the best of the authors’ knowledge, this paper sets for the first time a frontier between almost three decades where DDM evolved with no significative restrictions, grounded on innovations and market autoregulation, and an era where data privacy, anti-trust and competition and data sovereignty regulations converge to impose structural changes, requiring scholars and practitioners to rethink the roles of data at the strategic level of the firm.

This study advances a reconceptualization of data and information which overcomes normative understandings often contained in data policies at national and international levels. This study aims to propose a conceptual framework that moves beyond subject- and collective-centric normative understandings.

To do so, this study discusses the European Union (EU) and China’s approaches to data-driven technologies highlighting their similarities and differences when it comes to the vision underpinning how tech innovation is shaped.

Regardless of the different attention to the subject (the EU) and the collective (China), the normative understandings of technology by both actors remain trapped into a positivist approach that overlooks all that is not and cannot be turned into data, thus hindering the elaboration of a more holistic ecological thinking merging humans and technologies.

Revising the philosophical and political debate on data and data-driven technologies, a third way is elaborated, i.e. federated data as commons. This third way puts the subject as part by default of a collective at the centre of discussion. This framing can serve as the basis for elaborating sociotechnical alternatives when it comes to define and regulate the mash-up of humans and technology.

This study aims to investigate the merits of the unified model of task-specific motivation (UMTM) in predicting transfer of training and to investigate (relationships between) changes in UMTM components over time. In doing so, this study takes the multidimensionality of transfer motivation into account.

The authors collected data among 514 employees of the judiciary who filled in the UMTM questionnaire directly after the training and after three weeks. The data were analyzed by means of structural equation modelling.

The outcomes show that transfer motivation predicts transfer intention and transfer of training over time. Moreover, the study shows that (change in) transfer motivation is predicted by (change in) personal and contextual factors identified by the UMTM as antecedents of motivation.

This study describes the first longitudinal evaluation of the UMTM in the literature and shows its applicability for predicting transfer of training. It is also one of the few studies that investigate transfer motivation multidimensionally and the role it plays for transfer of training. As such, this study informs other transfer of training models about the nature of transfer motivation and how transfer of training could be predicted.

Patronage of local footwear have not been encouraging in Nigeria despite recent investments. The purpose of the study is to evaluate celebrity endorsement and customer patronage of small and medium-scale enterprises (SMEs) products in African context, with focus on trustworthiness, expertise, attractiveness, respect and similarity (TEARS) model.

The research was designed as a descriptive survey. An online structured questionnaire was applied for data collection. Cronbach Alpha and content validity were used for reliability and validity, respectively. TEARS model was used to ascertain key dimensions, and Pearson correlation coefficient and logistic regression were applied into the analysis.

The findings reveal that celebrity endorsement is not associated with patronage of local footwears, though TEARS model analysis indicates the direction of consumers rating on celebrity endorsement. Factors such as recommendation and quality impact the consumer willingness to buy local footwear.

The small sample size calls for caution in generalization.

The study suggests that although the TEARs model is viable, all the dimensions are mutually exclusive. However, this depends on the characteristics of the brand. In driving patronage, managers must pay attention to personal and non-personal cues such as price, quality and source of information about their brand.

The originality is buttressed from the value it provides for local product production and patronage. The significant factors are indicated as key to addressing low patronage.

Gathering knowledge regarding personality traits has long been the interest of academics and researchers in the fields of psychology and in computer science. Analyzing profile data from personal social media accounts reduces data collection time, as this method does not require users to fill any questionnaires. A pure natural language processing (NLP) approach can give decent results, and its reliability can be improved by combining it with machine learning (as shown by previous studies).

In this, cleaning the dataset and extracting relevant potential features “as assessed by psychological experts” are essential, as Indonesians tend to mix formal words, non-formal words, slang and abbreviations when writing social media posts. For this article, raw data were derived from a predefined dominance, influence, stability and conscientious (DISC) quiz website, returning 316,967 tweets from 1,244 Twitter accounts “filtered to include only personal and Indonesian-language accounts”. Using a combination of NLP techniques and machine learning, the authors aim to develop a better approach and more robust model, especially for the Indonesian language.

The authors find that employing a SMOTETomek re-sampling technique and hyperparameter tuning boosts the model’s performance on formalized datasets by 57% (as measured through the F1-score).

The process of cleaning dataset and extracting relevant potential features assessed by psychological experts from it are essential because Indonesian people tend to mix formal words, non-formal words, slang words and abbreviations when writing tweets. Organic data derived from a predefined DISC quiz website resulting 1244 records of Twitter accounts and 316.967 tweets.

The study investigated the effect of marketing communications’ dimensions on brand loyalty in the banking sector.

The study adopted the quantitative research approach which relied on the explanatory design due to the nature of the hypotheses tested. The convenience sampling technique was used to pull 377 customers of a branch of a commercial bank in Ghana. Furthermore, the PLS-SEM technique was deployed to assess the measurement model and test the research hypotheses.

Results show that the following dimensions of marketing communications are significant predictors of brand loyalty: direct marketing, public relations and sales promotion. The exception is advertising, which had an inverse relation with brand loyalty.

The results provide significant pointers to banks’ management that they should deploy a variety of marketing communication channels other than intensive advertising to reach and persuade customers.

The study illustrates the latest effort to extensively provide insights into how commercial banks could leverage marketing communication tools to sustain loyalty in an emerging economy that is intensively competitive.

The purpose of this paper is to explore the concept of brand hate in detail which is the extreme negative emotion toward brands, by giving a comprehensive explanation concerning how brand hate evolves in consumers. More specifically, antecedents of brand hate are empirically assessed in this study.

This study used primary data from 250 fast food brand consumers in Pakistan. Multiple regression analysis in SPSS was used to test the hypotheses related to the antecedents of brand hate.

Results indicate that brand hate is instigated by five antecedents, which are negative past experience, symbolic incongruity, poor relationship quality, ideological incompatibility and rumor, with rumor being the biggest instigator.

Antecedents of brand hate are assessed theoretically and empirically in this study which helps in understanding the true form of brand hate. More specifically, poor relationship quality and rumor are presented as the antecedents of brand hate according to the recommendations of the theory of hate.

El objetivo de este trabajo es explorar en detalle el concepto de odio a la marca, que es la emoción negativa extrema hacia las marcas, dando una explicación completa sobre cómo evoluciona el odio a la marca en los consumidores. Más específicamente, en este estudio se evalúan empíricamente los antecedentes de odio a la marca.

Este estudio utilizó datos primarios de 250 consumidores de marcas de comida rápida en Pakistán. El análisis de regresión múltiple en SPSS se utiliza para probar las hipótesis relacionadas con los antecedentes del odio a la marca.

Los resultados indican que el odio a la marca viene motivado por cinco antecedentes que son una experiencia pasada negativa, la incongruencia simbólica, la mala calidad de la relación, la incompatibilidad ideológica y el rumor negativo, siendo el rumor el mayor antecedente.

En este estudio se evalúan teórica y empíricamente los antecedentes del odio a la marca, lo que ayuda a comprender la verdadera forma de odio a la marca. Más específicamente, la mala calidad de la relación y el rumor se presentan como los antecedentes del odio a la marca de acuerdo con las recomendaciones de la teoría del odio.

Odio a la marca, gestión de marca, relación con el cliente

Trabajo de investigación