Browsing by Author "Antucheviciene, Jurgita"

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    Effect of integration of green constructs and traditional constructs of brand on green purchase intention of customers
    (Technical university of Liberec, Czech Republic, 2017-10-02) Esmaeili, Ahmad; Sepahvand, Akbar; Rostamzadeh, Reza; Joksiene, Izolda; Antucheviciene, Jurgita; Ekonomická fakulta
    The urgent concerns for environmental issues and growing demand for green products have made companies pay much more attention to green marketing. Although, many companies invest in green marketing, but not all of them gain as much as they invest. Most of failures of investments in green marketing are rooted in the fact that customers doubt both the real green performance of these products and the real intention of companies regarding green products. This research, being quantitative in nature, attempts to investigate the impact of traditional branding constructs (perceived quality of the brand, credibility of the brand) and green branding constructs (perceived value of a green brand, the green brand image, and brand equity) on the green purchase intention of customers. The hypotheses have been developed in the form of a conceptual model to investigate the relationship of these constructs. The research focuses on consumers of certain liquid washing detergent products. All the data were collected using questionnaires and the analysis of the data was conducted utilizing LISREL 8 and SPSS 16. The results indicate that perceived brand quality has a positive impact on the perceived value of a green brand, brand credibility, and brand image. In addition, green brand value and green brand image have a positive impact on brand equity. This research can serve as validation of the constructs to fill the gap in the investigation of green brand dimensions. Further analysis shows that green brand equity has a meaningful impact on the green purchase intention of the customers, however the impact of brand credibility on brand equity has not been proved.
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    Internet of things and its challenges in supply chain management; a rough strength-relation analysis method
    (Technická Univerzita v Liberci, 2018-06-28) Pishdar, Mahsa; Ghasemzadeh, Fatemeh; Antucheviciene, Jurgita; Saparauskas, Jonas; Ekonomická fakulta
    Internet of Things application (IOT) in supply chain management is becoming imperative and can shape a strategic competitive advantage. Albeit, different challenges appear through this application, most of the previous studies consider less about these challenges and focus on the advantages of IOT. To overcome this defect, different challenges that a supply chain may face as whole are determined based on systematic literature review and expert opinions. Then, a rough group decision-making and trial evaluation laboratory (DEMATEL) is applied. Advantages of the proposed model are that both internal strength and external influence of challenges and also vagueness and ambiguity of experts’ opinions are simultaneously noticed to completely show the importance of these challenges. The results show that challenges such as lack of strategy and scenario planning in IOT, storage issues, lack of security and lack of privacy are of great importance. So, these challenges should have a higher priority in attracting attention and resources. These results help managers to be equipped to face with main challenges in their path toward IOT in their supply chains. Accordingly some practical suggestions for managers are discussed in this paper, such as starting the journey toward IOT step by step, planning for a data storage system which is appropriate for big data, setting up a security policy to prevent out-coming problems caused by lack of security and privacy inherited by IOT, conducting a privacy or security risk assessment, minimizing the data collection and retain and testing the security measures before launching the products, and establishment of a legal framework to construct a problem-solving network in such a messed up and dynamic environment for processing such complicated huge data.
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    Sustainable Construction Supplier Selection by a Multiple Criteria Decision-making Method with Hesitant Linguistic Information
    (Technická Univerzita v Liberci, ) Liao, Huchang; Ren, Ruxue; Antucheviciene, Jurgita; Šaparauskas, Jonas; Al-Barakati, Abdullah; Ekonomická fakulta
    Within the context of resource constraints and ecological environment imbalance, the adoption of green suppliers can help construction enterprises achieve sustainable development and improve their competitiveness. The selection of sustainable construction suppliers is a multi-criteria decision-making problem since multiple factors should be considered. The increasingly complex decision-making environment makes it difficult for evaluators to give accurate evaluation values. In this regard, the hesitant fuzzy linguistic term set is a qualitative evaluation tool to represent the comprehensive linguistic evaluation values of experts by considering the hesitancy behaviors of experts. In this paper, a scientific multi-criteria decision-making model based on the improved Stepwise Weight Assessment Ratio Analysis (SWARA) method and the double normalization-based multi-aggregation (DNMA) method in the hesitant fuzzy linguistic environment is proposed. A new distance measure is proposed to measure the differences between hesitant fuzzy linguistic term sets with different lengths without changing the original evaluation information of experts. The proposed distance measure is applied to the proposed multi-criteria decision-making model. After improving the calculation steps of the traditional SWARA method, we can determine the weights of criteria effectively through our proposed model. To verify the applicability of the proposed method, we implement it to select sustainable building suppliers. The effectiveness of the method is verified by sensitivity analysis. We also compare the results obtained by our method and those derived by the Weight Aggregated Sum Product ASsessment (WASPAS) method and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. The proposed method have a strong applicability to solve the sustainability-related decision problems given that it can effectively determine the weights of criteria and flexibly meet the needs of decision-makers by adjusting the coefficient.