Search results

The effects of board composition on performance have long been discussed in management research using fractionalization measures. In this study, we propose an alternative measurement approach based on board polarization.

Using an exploratory analysis and applying the polarization measure to German Deutscher Aktienindex (DAX)-, Midcap-DAX (MDAX)- and Small Cap-Index (SDAX)-listed companies, this paper applies the polarization index to examine the relationship between board diversity and performance.

The results show that the polarization concept is well suited to measure principal-agent problems between the members of the management and supervisory boards. We reveal that board polarization is negatively associated with firm performance, as measured by return on investment (ROI).

This exploratory study shows that the measurement of board polarization can be linked to performance differences between companies, which offers promising starting points for further research.

This paper aims to overview the need for tobacco harm reduction, the consumer products that facilitate tobacco harm reduction and the barriers to its implementation. The worldwide endemic of tobacco smoking results in the death of over seven million smokers a year. Cigarette quit rates are very low, from 3%–12%, and relapse rates are high, from 75%–80% in the first six months and 30%–40% even after one year of abstinence. In addition, some smokers do not desire to quit. Cigarette substitution in tobacco harm reduction is one strategy that may reduce the burden of morbidity and mortality.

This review examines the displacement of smoking through substitution of non-combustible low-risk products such as snus, heated tobacco products and e-cigarettes.

Toxicological testing, population studies, clinical trials and randomized controlled trials demonstrate the potential reductions in exposures for smokers. Many barriers impede the implementation of product substitution in tobacco harm reduction. These products have been subjected to regulatory bans and heavy taxation and are rejected by smokers and society based on misperceptions about nicotine, sensational media headlines and unsubstantiated fears of youth addiction. These barriers will need to be addressed if tobacco harm reduction is to make the maximum impact on the tobacco endemic.

This review provides the rationale for tobacco harm reduction, evaluates the current products available and identifies the barriers to implementation.

As evident from the literature review, the research on cyber security performance is centered on security metrics, maturity models, etc. Essentially, all these are helpful for evaluating the efficiency of cyber security organization but what matters is how the factors of internal efficiency affect the business performance, i.e. the external effectiveness. The purpose of this research paper is to derive the factors of internal efficiency and external effectiveness of cyber security and develop impact model to identify the most and least preferred parameters of internal efficiency with respect to all the parameters of external effectiveness.

There are two objectives for this research: Deriving the factors of internal efficiency and external effectiveness of cyber security; Developing a model to identify the impact of internal efficiency factors on the external effectiveness of cyber security since there is not much evidence of research in defining the factors of internal efficiency and external effectiveness of cyber security, the authors have chosen grounded theory methodology (GTM) to derive the parameters. In this study emic approach of GTM is followed and an algorithm is developed for administering the grounded theory research process. For the second research objective survey methodology and rank order was used to formulate the impact model. Two different samples and questionnaires were designed for each of the objectives.

For the objective 1, 11 factors of efficiency and 10 factors of effectiveness were derived. These are used as independent and dependent variable respectively in the later part of the research for the second objective. For the objective 2 the impact models among independent and dependent variables were formulated to find out the following. Most and least preferred parameters lead to internal efficiency of cyber security organization to identify the most and least preferred parameters of internal efficiency with respect to all the parameters external effectiveness.

The factors of internal efficiency and external effectiveness constructed by using grounded theory cannot remain constant in the long run, because of dynamism of the domain itself. Over and above this, there are inherent limitations of the tools like grounded theory, used in the research. Few important limitations of GTM are as below in grounded theory, it is comparatively difficult to maintain and demonstrate the rigors of research discipline. The sheer volume of data makes the analysis and interpretation complex, and lengthy time consuming. The researchers’ presence during data gathering, which is often unavoidable and desirable too in qualitative research, may affect the subjects’ responses. The subjectivity of the data leads to difficulties in establishing reliability and validity of approaches and information. It is difficult to detect or to prevent researcher-induced bias.

The internal efficiency and external effectiveness factors of cyber security can be further correlated by the future researchers to understand the correlations among all the factors and predict cyber security performance. The grounded theory algorithm developed by us can be further used for qualitative research for deriving theory through abstractions in the areas where there is no sufficient availability of data. Practitioners of cyber security can use this research to focus on relevant areas depending on their respective business objective/requirements. The models developed by us can be used by the future researchers to for various sectoral validations and correlations.

Though the financial costs of a cyber-attack are steep, the social impact of cyber security failures is less readily apparent but can cause lasting damage to customers, employees and the company. Therefore, it is always important to be mindful of how the impact of cyber security affects society as well as the bottom line when they are calculating the potential impact of a breach. Underestimating either impact can destroy a brand. The factor of internal efficiency and external effectiveness derived by us will help stakeholder in focusing on relevant area depending on their business. The impact model developed in this research is very useful for focusing a particular business requirement and accordingly tune the efficiency factor.

During literature study the authors did not find any evidence of application of grounded theory approach in cyber security research. While the authors were exploring research literature to find out some insight into the factor of internal efficiency and external effectiveness of cyber security, the authors did not find concrete and objective research on this. This motivated us to use grounded theory to derive these factors. This, in the authors’ opinion is one of the pioneering and unique contribution to the research as to the authors’ knowledge no researchers have ever tried to use this methodology for the stated purpose and cyber security domain in general. In this process the authors have also developed an algorithm for administering GTM. Further developing impact models using factors of internal efficiency and external effectiveness has lots of managerial and practical implication.

Nowadays, more and more brands are developing their own virtual ambassadors for interactive communication and marketing with consumers. Exploring the interactive effectiveness of virtual brand ambassadors on consumer behavior is crucial to understanding the interactions between brands, virtual ambassadors and consumers as well as further increasing consumer engagement in AI-mediated interactive marketing.

This study investigated different interactive effects of virtual ambassadors on consumer behavior in terms of virtual ambassadors’ anthropomorphism, virtual experience and consumer behavior through a mixed method of questionnaires and semi-structured interviews.

The results indicate that consumers’ sharing, reviewing and purchasing behavior is significantly and positively influenced by virtual ambassadors’ anthropomorphism and virtual experience. In addition, specific anthropomorphic features and virtual experiences were discussed in detail.

This study helps brands develop and manage their virtual ambassadors and consumers in AI-mediated interactive marketing and communication.

Projecting the population distribution in geographical regions is important for many applications such as launching marketing campaigns or enhancing the public safety in certain densely populated areas. Conventional studies require the collection of people’s trajectory data through offline means, which is limited in terms of cost and data availability. The wide use of online social network (OSN) apps over smartphones has provided the opportunities of devising a lightweight approach of conducting the study using the online data of smartphone apps. This paper aims to reveal the relationship between the online social networks and the offline communities, as well as to project the population distribution by modeling geo-homophily in the online social networks.

In this paper, the authors propose the concept of geo-homophily in OSNs to determine how much the data of an OSN can help project the population distribution in a given division of geographical regions. Specifically, the authors establish a three-layered theoretic framework that first maps the online message diffusion among friends in the OSN to the offline population distribution over a given division of regions via a Dirichlet process and then projects the floating population across the regions.

By experiments over large-scale OSN data sets, the authors show that the proposed prediction models have a high prediction accuracy in characterizing the process of how the population distribution forms and how the floating population changes over time.

This paper tries to project population distribution by modeling geo-homophily in OSNs.

One popular method to assess discriminant validity in structural equation modeling is the heterotrait-monotrait ratio of correlations (HTMT). However, the HTMT assumes tau-equivalent measurement models, which are unlikely to hold for most empirical studies. To relax this assumption, the authors modify the original HTMT and introduce a new consistent measure for congeneric measurement models: the HTMT2.

The HTMT2 is designed in analogy to the HTMT but relies on the geometric mean instead of the arithmetic mean. A Monte Carlo simulation compares the performance of the HTMT and the HTMT2. In the simulation, several design factors are varied such as loading patterns, sample sizes and inter-construct correlations in order to compare the estimation bias of the two criteria.

The HTMT2 provides less biased estimations of the correlations among the latent variables compared to the HTMT, in particular if indicators loading patterns are heterogeneous. Consequently, the HTMT2 should be preferred over the HTMT to assess discriminant validity in case of congeneric measurement models.

However, the HTMT2 can only be determined if all correlations between involved observable variables are positive.

This paper introduces the HTMT2 as an improved version of the traditional HTMT. Compared to other approaches assessing discriminant validity, the HTMT2 provides two advantages: (1) the ease of its computation, since HTMT2 is only based on the indicator correlations, and (2) the relaxed assumption of tau-equivalence. The authors highly recommend the HTMT2 criterion over the traditional HTMT for assessing discriminant validity in empirical studies.