Network analysis of the Caucasus’ image

Destination image is influenced by many factors, including destination promotion materials, the mass media as a general familiarity agent, the perceivers’ own characteristics and even researchers’ methodological choices. To isolate and minimize the impact of research on destination image, different qualitative and quantitative designs and analysis techniques have been utilized. However, no previous study utilized the network analysis technique, which may be useful to reveal a picture of destination image with the interconnections and hidden dynamisms of dimensions as well as its correlates. The present study applies this technique on qualitative data from an online sample of Americans on their perceptions of a relatively remote and unfamiliar destination, the Caucasus region, in order to hone in on the dramatic impact of mass media on destination image. Results revealed networks of meanings with residue of mass media messages about Boston bombing, with some differences among different genders and education levels.     

Risk identification and prioritization in banking projects of payment service provider companies: an empirical study

Identifying risks and prioritizing is important for payment service provider (PSP) companies to get banking projects and gain more market share. However, studies regarding the identification of risks and causal relationships are insufficient in the Iranian PSP industry and the industry is unique because of its characteristics. In this study, 30 experts involved with PSP companies are employed as the research sample. Eleven key risks and Forty-six sub-risks are also identified. Subsequently, the fuzzy decision-making trial and evaluation laboratory technique is applied to determine the effective and affected risks and the severity of their effects on each other. Finally, all risks are ranked. Due to the internal interrelationships of the main risks, the weight of each risk is calculated via the fuzzy analytic network process. As the second-level risks have no significant interrelationships, they are ranked via the fuzzy analytical hierarchy process. Moreover, the best-worst method is used to ensure that the obtained rankings are reliable. This study identifies the risks affecting the loss of banking projects and determines the impacts of these risks on each. A sensitivity analysis is then conducted on the weights of the criteria, and the results are compared.