دانلود مقاله ISI انگلیسی شماره 950
ترجمه فارسی عنوان مقاله

توسعه یک تجزیه و تحلیل SWOT مبتنی بر ANP فازی برای صنعت هواپیمایی در ترکیه

عنوان انگلیسی
Development of a fuzzy ANP based SWOT analysis for the airline industry in Turkey
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
950 2012 11 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Expert Systems with Applications, Volume 39, Issue 1, January 2012, Pages 14–24

ترجمه کلمات کلیدی
تجزیه و تحلیل - مدیریت استراتژی -  منطق فازی - فازی -  فازی - تصمیم گیری چند معیاره - صنعت هواپیمایی -
کلمات کلیدی انگلیسی
Fuzzy logic, Fuzzy AHP, Fuzzy ANP, Multi-criteria decision making, Airline industry,
پیش نمایش مقاله
پیش نمایش مقاله  توسعه یک تجزیه و تحلیل SWOT مبتنی بر ANP فازی برای صنعت هواپیمایی در ترکیه

چکیده انگلیسی

Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis has been widely used to evaluate alternative strategies in order to determine the best one for given business setting. This study aims at providing a quantitative basis to analytically determine the ranking of the factors in SWOT analysis via a conventional multi-criteria decision making method, Analytic Network Process (ANP). The ANP method is preferred in this study because of its capability to model potential dependencies among the SWOT factors. The study presents uniqueness in the way it incorporates inherent vagueness and uncertainty of the human decision making process by means of the fuzzy logic. The proposed SWOT fuzzy ANP methodology was implemented and tested for the Turkish airline industry. The results showed that the SWOT fuzzy ANP is a viable and highly capable methodology that provides invaluable insights for strategic management decisions in the Turkish airline industry, and can also be used as an effective tool for other complex decision making processes.

مقدمه انگلیسی

The World Wide Web, described by Sir Tim Berners-Lee as “an interactive sea of shared knowledge..........made of the things we and our friends have seen, heard, believe or have figured out,” has drastically changed traditional marketing (Evans & McKee, 2010, p. xvii). Traditional marketing involves an information exchange in a one-way direction (e.g., television and radio commercials). On the contrary, web-based marketing involves two-way communication with customers while maintaining the push-messaging (Trusov, Bucklin, & Pauwels, 2009). Social media facilitate two-way communication and connect people on a mass scale. The collaborative technologies that now define contemporary marketplaces provide tremendous opportunities for new business initiatives across a wide range of applications. These social media technologies allow savvy businesses to connect with their customers and prosper through a two-way collaborating relationship. Social media sites are leveraging direct selling to reach social networks of family, friends, and co-workers, thus extending the reach of direct selling (Glenn, 2011). Social media comprise both the conduits and the content disseminated through interactions between individuals and organizations (Kietzman, Hermkens, McCarthy, & Silvestre, 2011). Despite all of the supposed benefits, selecting the right social media platform has been a daunting task for corporate marketers. This difficulty is due to: (i) the optimal frequency of posting; (ii) the fixed cost of establishing a social media presence; (iii) the average cost of creating a typical ‘engagement entry’ (e.g., a Facebook posting, a YouTube video, a tweet, etc.) on a social media site; and (iv) the expected cost of building a reasonable follower audience or fan base. Although the social media platform selection problems are inherently complex problems with multiple and often conflicting criteria, no analytical social media platform evaluation and selection model has been proposed in the literature. Most existing models are limited to simple classification charts categorizing the different types of social media engagements (McLellan, 2010). There is a need for a more systematic and analytical framework for social media platform evaluation and selection. We propose a novel analytical framework for social media platform selection. The proposed hybrid framework integrates the Analytic Network Process (ANP) with fuzzy set theory and the COmplex PRoportional ASsessment of alternatives with Grey relations (COPRAS-G) method. The ANP and fuzzy set theory are used to determine the importance weight of the social media platform selection criteria in a fuzzy environment. The COPRAS-G method is used to rank and select the most suitable social media platform. The remainder of this paper is organized as follows. In Section 2 we review the relevant literature on social media marketing, Multi-Attribute Decision Making (MADM) and the Analytic Network Process (ANP), fuzzy set theory and the COmplex PRoportional ASsessment of alternatives with Grey relations (COPRAS-G) method. In Section 3 we provide the details of the hybrid method proposed in this study. In Section 4 we present a real-world case study to demonstrate the applicability of the proposed framework and exhibit the efficacy of the procedures and algorithms. In Section 5 we present our conclusions and future research directions.

نتیجه گیری انگلیسی

The recent developments in computers and information technology have brought both opportunities and challenges in the global and boundary-less world. Marketing managers are faced with a dynamic and interconnected international environment and social media sites have become important tools for businesses. Many organizations now actively use social media platforms to promote and market their products and services. Unlike conventional marketing tools, social media applications allow users to have more control of their choices by posting comments, sharing information, or praising or criticizing products and services. Although traditional media are not disappearing, it is clear that major marketers are shifting their budgets into new social media marketing opportunities and applications. Traditional marketing, involving exchange of information in one direction, can no longer help companies introduce all aspects of their products and show customers that their needs are important. Social media facilitate two-way communication and connect customers on a mass scale. Despite these benefits, selecting the right social media platform has been a difficult task because these problems are complex with multiple and often conflicting criteria. Most existing social media selection models are limited to simple classification charts categorizing the different types of social media engagements or simple decision trees highlighting the key decisions one must make when choosing the right platform. We proposed a novel analytical framework for social media platform selection. The proposed hybrid framework integrates the ANP with fuzzy set theory and the COPRAS-G method. The ANP and fuzzy set theory were used to determine the importance weight of the social media platform selection criteria. The COPRAS-G method was used to rank and select the most suitable social media platform. We presented a real-world case study and demonstrated the applicability of the proposed framework. The proposed framework is: (1) structured and systematic with step-by-step and well-defined procedures; (2) simple and transparent with a straightforward computation process; (3) rational and logical with a sound mathematical and theoretical foundation; (4) supportive and informative with a scalar value that identifies both the best and worst social media platform simultaneously; (5) realistic and practical with the ability to deal with impreciseness and vagueness in real-world social media platform assessment problems; and (6) versatility and flexibility with the ability to be applied to other multi-criteria prioritization problems. A stream of future research can extend our method by developing other hybrid approaches for the integrated use of our distance measure, not only for hybrids of different MADM methods but also for hybrids of multi-attribute value theory and numerical optimization.