Search results

The housing/real estate sector is one of the most important sectors in any country. However, existing marketing literature on the home buying behavior and the decision-making process is still in the early stage of development. The purpose of this study is to examine the home buying behavior from the consumers’ perspective in a high-context culture, namely, Kyrgyzstan and its managerial and/or public policy implications to other countries which are at a similar level of socio-economic development as Kyrgyzstan.

Using a questionnaire, data for the study (n = 300) is collected from households in Bishkek, Kyrgyzstan. Personal interviews were used to collect data from the four administrative regions of Bishkek.

Results of this study show that the physical, environmental and financial dimensions of the homes influenced consumers’ home buying intentions. A few statistically significant differences in terms of preferences for the proximity of the property to schools and shopping districts, having public sewer and water connections, and safety characteristics of the neighborhood were found between the first-time homebuyers and the repeat homebuyers.

The most important limitation of the study is the use of convenience sampling. Although the sample size is reasonably large, the selection of the responses was done based on using convenience and connections. Representativeness of the results may be limited.

Along with the physical, environmental and financial dimensions of the homes, home buying is a high-involvement decision; it is not as much of an emotional purchase but rather a main residence and a good long-term value for Kyrgyz households. Both marketing and social stimuli did not have any statistically significant effect on purchase intentions. Therefore, housing and real estate developers should focus on understanding how their offering meets individual customers’ tangible and intangible expectations and assist them in their highly involved decision-making process.

To the best of the authors’ knowledge, this study is the first to conduct an empirical study to analyze the home buying decisions of Kyrgyz households. This study contributes to marketing literature by filling the existing gaps in understanding various facets of the high-context consumers’ home buying decision-making.

This paper develops a theoretical model that analyzes the decision problem the landowner has to face between the construction of second homes and hotels. The starting point implies verifying that for a given tourist destination, the land available for the construction of accommodation is limited. For this reason, when choosing between building second homes or building hotels, many factors influence the decision model. The theoretical mechanism generalizes the model introduced in Brida and Boffa (2010) and is based on a four-stage sequential game with four players. From the results of the model, the authors conclude that it is optimal from the social point of view both to build a hotel and to build a second home because both generate added value during the year. For this reason, the construction of second homes should be taken into account in the planning policy of the tourist destination. This arises from considering that second homes, as they remain occupied all year like hotels, in certain tourist destinations, do not generate seasonality.

In view of the complexity of supply chain management (SCM) in the insurance industry, to the best of the authors’ knowledge, this paper was the first to use symmetrical and asymmetrical methos to examine how the insurer’s service quality and SCM can be configurated to explain the relationships between the insurance companies and brokers as the intermediaries. This study positions insurance brokers as the insurance companies’ customers and supply chain partners, aims to examine the relationships between service quality, SCM and relationship quality.

This paper undertook two studies and used two methods to examine how the insurer’s service quality and SCM can be configurated to explain the relationships between the insurance companies and brokers as the intermediaries. Both symmetrical and asymmetrical analyses were performed including regression and fuzzy-set qualitative comparative analysis (fsQCA).

The results from symmetrical analyses and fsQCA from two countries show substantial differences in how service quality and SCM affect relationship quality. In particular, fsQCA show that all service quality dimensions are important antecedent conditions of relationship quality for Portuguese brokers. Interestingly for Irish brokers, the combination of assurance, responsiveness and the insurer’ empathy conjunctively accounted for their satisfaction, whereas none of these quality factors are related to their commitment and trust. All SCM factors are important to explain the brokers’ relationship quality with their chosen insurers for both countries.

This study contributes to three areas of research: service quality, SCM and relationship marketing. Firstly, this study used an asymmetrical approach to providing insights into the effect of service quality dimensions by showcasing how these dimensions were configurated to explain the outcome of interest, rather than examining their symmetrical path coefficients. Secondly, this study identified the key factors of SCM in the insurance industry and how these factors can be configurated through Boolean algebra to explain relationship quality between supply chain partners. Finally, this study has implications for relationship marketing research.

As the study was conducted with the insurance brokers in Portugal and Ireland, the findings have implications for the insurance companies for the two countries. As different service quality factors and SCM exert different effects on relationship quality, the insurance companies should look into these factors to modify their current practice to improve relationship quality with their brokers.

Theoretically, to the best of the authors’ knowledge, this is the first study to approach from intermediaries to address effectiveness of SCM. Methodologically, to the best of the authors’ knowledge, this is the first study to use fsQCA – a case-based approach to understand SCM and relationship quality between stakeholders.

A zero-day vulnerability is a complimentary ticket to the attackers for gaining entry into the network. Thus, there is necessity to device appropriate threat detection systems and establish an innovative and safe solution that prevents unauthorised intrusions for defending various components of cybersecurity. We present a survey of recent Intrusion Detection Systems (IDS) in detecting zero-day vulnerabilities based on the following dimensions: types of cyber-attacks, datasets used and kinds of network detection systems.

Purpose: The study focuses on presenting an exhaustive review on the effectiveness of the recent IDS with respect to zero-day vulnerabilities.

Methodology: Systematic exploration was done at the IEEE, Elsevier, Springer, RAID, ESCORICS, Google Scholar, and other relevant platforms of studies published in English between 2015 and 2021 using keywords and combinations of relevant terms.

Findings: It is possible to train IDS for zero-day attacks. The existing IDS have strengths that make them capable of effective detection against zero-day attacks. However, they display certain limitations that reduce their credibility. Novel strategies like deep learning, machine learning, fuzzing technique, runtime verification technique, and Hidden Markov Models can be used to design IDS to detect malicious traffic.

Implication: This paper explored and highlighted the advantages and limitations of existing IDS enabling the selection of best possible IDS to protect the system. Moreover, the comparison between signature-based and anomaly-based IDS exemplifies that one viable approach to accurately detect the zero-day vulnerabilities would be the integration of hybrid mechanism.

IoT has a wide range of applications in the health-care sector and has captured the interest of many academic and industrial communities. The health IoT devices suffer from botnet attacks as all the devices are connected to the internet. An army of compromised bots may form to launch a DDoS attack, steal confidential data of patients and disrupt the service, and hence detecting this army of bots is paramount. This study aims to detect botnet attacks in health IoT devices using the deep learning technique.

This paper focuses on designing a method to protect health IoT devices from botnet attacks by constantly observing communication network traffic and classifying them as benign and malicious flow. The proposed algorithm analyzes the health IoT network traffic through implementing Bidirectional long-short term memory, a deep learning technique. The IoT-23 data set is considered for this research as it includes diverse botnet attack scenarios.

The performance of the proposed method is evaluated using attack prediction accuracy. It results in the highest accuracy of 84.8%, classifying benign and malicious traffic.

The proposed method constantly monitors the health IoT network to detect botnet attacks and classifies the traffic as benign or attack. The system is implemented using the BiLSTM algorithm and trained using the IoT-23 data set. The diversity of attack scenarios of the IoT-23 data set demonstrates the proposed algorithm's competence in detecting botnet types in a heterogeneous environment.

The Mongol invasion caused widespread destruction in many cities; this research studies the destruction course of cities after the Mongol invasion and their reconstruction during the reform period, the change that it brought to the cityscapes of Iranian cities and the difference between the urbanscape of the cities that flourished or were re-established after these destructions with the cities prior to them.

The method of research used is historical interpretation/analysis. The historical texts of pre-Mongolian Persia and texts from the Ilkhanid era are studied, references to the shapes and appearances of Iranian cityscapes are classified, and with the help of contemporary interpretations and existing physical evidence, the urbanscape of these two periods are redrawn and compared to each other.

The selection of scenic meadows to build the city, the presence of many gardens in the urban patterns and the construction of satellite towns around large cities have been the effects of the Mongol tradition of (Yurt) tent-dwelling on Iranian cities during the reforms. The declining population and the massive migration of artists together with the rethinking of the rulers made the existence of dense cities with multi-storey houses less likely. The tradition of pre-designing the city and buildings and designing open and right-angled pathways continued after the Mongol invasion.

The prevailing belief is that during the Mongol era, only the destruction of cities took place and the Mongols did not create any cities and had no influence on urban development. This research aims to challenge that.