Научная статья на тему 'Conjoint analysis and online forums on cultural heritage in Albania – analysing TripAdvisor reviews'

Conjoint analysis and online forums on cultural heritage in Albania – analysing TripAdvisor reviews Текст научной статьи по специальности «СМИ (медиа) и массовые коммуникации»

CC BY
511
25
i Надоели баннеры? Вы всегда можете отключить рекламу.
Ключевые слова
Culture heritage / marketing / Albania / conjoint analysis

Аннотация научной статьи по СМИ (медиа) и массовым коммуникациям, автор научной работы — Roshi Elenita

In this paper I shed light on the complex relations between market segmentation of culture heritage and market segmentation in Albania based on: 1) online reviews in TripAdvisor and 2) a survey with 75 foreign visitors. The main research method was based on the full profile conjoint analysis in both survey designs. In the first phase of the research different attributes were identified based on the repetitions and main subject of reviews on TripAdvisor. From these were selected four attributes that were similar to those of marketing mix: culture heritage product, price, place, promotion and period of time. These attributes were measured individually and in interaction with each other. SPSS program was helpful during the conjoint analysis by using the orthogonal design. Four different attributes (product, price, place and period of time) there were given different values, that resulted in 25 different combinations. Since this number was too large, were taken in consideration only those categories that were more logical and were compatible with the official data. The final results derived from a survey with foreign tourist in Albania realized during the March – April 2017 resulted that visitors were more interested in to travel from the period from March – September, like to have cheap or medium prices and have in interests in every part of Albania and especially to its history, culture and archaeology.

i Надоели баннеры? Вы всегда можете отключить рекламу.
iНе можете найти то, что вам нужно? Попробуйте сервис подбора литературы.
i Надоели баннеры? Вы всегда можете отключить рекламу.

Текст научной работы на тему «Conjoint analysis and online forums on cultural heritage in Albania – analysing TripAdvisor reviews»

Section 2. Marketing

Roshi Elenita, PhD, Student University of Tirana PhD student in Marketing, the Faculty of Economics Email: elenitaroshi@yahoo.com

CONJOINT ANALYSIS AND ONLINE FORUMS ON CULTURAL HERITAGE IN ALBANIA - ANALYSING TRIPADVISOR REVIEWS

Abstract: In this paper I shed light on the complex relations between market segmentation of culture heritage and market segmentation in Albania based on: 1) online reviews in TripAdvisor and 2) a survey with 75 foreign visitors. The main research method was based on the full profile conjoint analysis in both survey designs. In the first phase of the research different attributes were identified based on the repetitions and main subject of reviews on TripAdvisor. From these were selected four attributes that were similar to those of marketing mix: culture heritage product, price, place, promotion and period of time. These attributes were measured individually and in interaction with each other. SPSS program was helpful during the conj oint analysis by using the orthogonal design. Four different attributes (product, price, place and period of time) there were given different values, that resulted in 25 different combinations. Since this number was too large, were taken in consideration only those categories that were more logical and were compatible with the official data. The final results derived from a survey with foreign tourist in Albania realized during the March - April 2017 resulted that visitors were more interested in to travel from the period from March - September, like to have cheap or medium prices and have in interests in every part of Albania and especially to its history, culture and archaeology.

Keywords: Culture heritage, marketing, Albania, conjoint analysis.

1. Introduction ries of multiculturalism in the beginning of 1990 s,

Conjoint analysis has been considered as one of the individual choice and social media, the ap-of the best marketing methods to study the cus- proach on studding visitors of cultural heritage was tomer's preferences on different topics and market based mainly on quantitative, qualitative surveys or segments. Widely used for the exploration of cus- mixed research methods. The main problem from tomer's inclinations in different service industries these approaches was that their analyses were mainly such as industrial goods, financial services, trans- 'descriptive in nature rather than predictive' [2, 1]. portation, auto insurance policies [1, 8], it seemed 'Descriptive information is useful to characterize uneven in the field of cultural heritage. This has demographics, usage patterns, and attitudes of in-happened for many reasons. The first origin of the dividuals. Beyond descriptive information, managproblem is considered the mere nature of culture ers heed survey research tools that can predict what heritage as being at the same time a very large and consumers will buy when faced with the variety of specific field of research. With the emerging of theo- brands available and myriad product characteristics.

It is precisely due to this focus that conjoint or trade-off analysis has become so popular over the last three decades' [2]. On the other hand, the marketing research in Eastern European countries such as Albania is novel and undeveloped. Many data regarding culture heritage and the main preferences of the visitors are confused or just missing. For these reasons I have chosen to focus my research to on one 'of the leading platforms for travel-related reviews' [3] such as TripAdvisor. Nowadays 'tens of millions of travellers share travel experiences through online communities such as TripAdvisor, Yahoo! Travel, Igougo, and Lonelyplanet' [4]. Tripadvisor has been founded in 2000 and today is the most popular travel community. Currently, this platform includes over 435 million reviews for 1.9 million accommodations, 4.2 million restaurants, and 730,000 attractions, and the platform enjoys 390 million average monthly unique visitors reflecting an 11% growth [6]. However, reviews related to Albania are modest. In total it is mentioned in only 1701 topics.

Generally has been proved that 'potential travellers have difficulties in assessing quality of tourism products prior to experiencing them. One way to gain confidence in a tourism product is to search information about the product prior to purchase. The information process of potential travellers is initiated from searching internal sources such as their experiences. When internal information is insufficient, searching will move to external sources. Today, travellers use various types and amounts of information - online and offline. Among various online information sources, community websites are becoming increasingly important. These global platforms enable travellers to share their experiences - posting reviews - with like-minded others [4]. 'In fact, social media content is perceived very often as more trustworthy compared to official tourism websites or mass media advertising' [6].

2. Problem definition

'The internet has been used as a medium for data collection since about 1995, although its rapid growth can mostly be identified as being from

1999 onwards, and its ascendancy in terms of quantitative data collection has only happened over the last three years' [7]. According to the Albanian official statistics the penetration of internet in the Albanian population is 62, 8% for the year 2016. It consist of 0.1% of the internet users in the world [6, 187]. The other internet platform for travellers lonely planet describes the internet acces as 'free wi-fi is ubiquitous in all but the most basic hotels. In larger towns many restaurants also offer free access' [9]. Thus it makes it easy for tourists to publish their reviews online whenever they are placed in the Albanian territory. It is important to assess that in the most of the hotels internet is free and without payment.

Albania offers many possibilities for the culture heritage visitors. 'Located in the heart of the Mediterranean region, north of Greece and east of Italy, Albania is situated at the crossroads of multiple cultures and many invading armies. Over the past two millennia, this mountainous country was part ofthe Roman, Byzantine, and Ottoman empires until its independence in 1912' [10, 312]. The communist approach was mainly ideological and restricted the number of visitors [11, 539-555]. Many Albanian museums today have still the materialist interpretation of history in some of their parts. This is today one of the main hampers to reform culture heritage according to market economy rules. As Misiura points out 'in the heritage industry it is fast becoming recognized that heritage attractions and brands, in particular those that want repeat business (most of them do), must address the needs of their visitors/customers and that this focus should be a (on-going) priority from which the rest (targeting, interpretation, resource management, etc.) will follow. Heritage attractions or other heritage consumer brands must appeal to the aspirations, needs and motivations ofprospective and regular customers' [12, 81]. There are very few data regarding the preferences of the visitors of cultural heritage in Albania. The official data change from year in year and it is difficult to derive from them market segments or to identify regular foreign consumers.

Conjoint analysis helps us to collect data on culture heritage visitors in Albania and to construct alternatives referred to as concept profiles. 'In marketing contexts, concept profiles typically describe brands, products, or services. [...] Concept profiles may consist of verbal descriptions, although they may include pen-and-ink representations, physical mockups, or videotaped demonstrations. The primary reason for restricting the choice situation in this way is to ensure that respondents evaluate each profile with respect to the same information. Ambiguous and equivocal cues are removed so that all respondents have at their disposal the same information and no more. When the concept describes an economic choice alternative, the description usually includes price [13, 2]. This will help to base my research on the heritage tourist and visitor level and to collect data on their preferences. 'Albania's heritage has always been defined in a topdown manner; experts define the list of potential monuments, which are examined and certified and then added to the national list of protected sites. This process addresses heritage on a national level, but often overlooks or willfully ignores the local implications of state-level action [10, 318]. For all these reasons it will be possible to get more specific data based on the conjoint analysis model and give better segments not only of culture heritage but also tourism in Albania.

3. Aims and research questions

The main aim of this paper is to determine the main attributes (characteristics) of the culture heritage in Albania as seen by the foreign visitors in Tripadvisor and their main preferences as surveyed with a help of a questionnaire. Through the conj oint analysis data and their results I want to be able to construct future recommendations for the managers of cultural heritage in Albania. Since 'conjoint results is the most valuable tool for managers. A market simulator uses the utility scores to predict which product alternatives respondents would choose within competitive scenarios. The predictions can be made not only for the few product alternatives

that were actually shown to respondents, but also for the often thousands or more potential combinations that were not shown' [2, 11]. Other aims of the paper include the fact that cultural heritage research field in Albania is still an unexplored field and needs to be adjusted to the new policies of the market economy.

4. Theoretical framework

'Several interdependent decisions are involved in the formulation of a marketing strategy for a brand (of a product or service). These include not only decisions about the product's characteristics but also its positioning, communication, distribution, and pricing to chosen sets of targeted customers' [1, 1]. 'Market segmentation is the process of dividing a total market (or sub-market) using the principles identified above in order to create one or more homogeneous groups or segments that can then be targeted effectively, based on the accessibility of these customers and the resources of the organization' [12, 79]. In the field of culture heritage many authors have suggested that 'the business of heritage must address a combination of biology, psychology and instinct in planning and marketing a heritage product, service or brand' [12, 79]. Travel reviews online communities such as TripAdvisor 'makes information easy to find, but difficult to process and judge' [4, 676]. The result is a decrease in search costs and an increase in cognitive costs. For the best selection among overflowing reviews, travellers need to put more cognitive efforts by remembering one review and comparing it with others. Thus, too much information increases cognitive costs such as anxiety about uncertain preferences, lack of expertise, and incorrect decision. As it is cognitively cumbersome for potential travellers to evaluate the quality of each review available in online communities, they may use extrinsic cues to judge quality. Lee et al suggest that 'in addition to price, brand, and country of origin that indicate product quality, reputation is another extrinsic cue indicating the quality of online merchants and online information

creators' [4]. However, other studies have found that 'just over one-third of complaints tended to juxtapose an overall negative evaluation with some type of positive appraisal, and that a similar proportion of the complaints made explicit reference to reviewer's expectations not being met' [14]. The researcher Vasquez found out that usually 'complaints often occurred as a larger speech act set, and (perhaps not surprisingly) in this particular context, complaints tended to co-occur more frequently with advice and recommendations rather than with other types of speech acts such as warnings or threats [14].

4.1. Merging marketing mix with culture heritage in TripAdvisor reviews

Conjoint Analysis has been considered as a Predictive Model ofChoice. This method was based in works of mathematical psychologists and statisticians Luce and Tukey (1964), and discrete choice methods came from econometrics, building upon the work ofMcFad-den (1974), 2000 Nobel Prize winner in economics. According to Orme (2010) 'marketers sometimes have thought (or been taught) that the word 'conjoint' refers to respondents evaluating features ofproducts or services [that were] 'considered jointly'. But as he point out 'in reality, the adjective "conjoint" derives from the verb 'to conjoin' meaning 'joined together. The key characteristic of conjoint analysis is that respondents evaluate product profiles composed of multiple conjoined elements (attributes or features). Based on how respondents evaluate the combined elements (the product concepts), we deduce the preference scores that they might have assigned to individual components of the product that would have resulted in those overall evaluations' [2, 29]. 'Back in the early 1970s, marketing academics (Green and Rao 1971) applied the notion of conjoint measurement, which had been proposed by mathematical psychologists (Luce and Tukey 1964), to solve these complex problems. The general idea was that humans evaluate the overall desirability ofa complex product or service based on a function of the value of its separate (yet conjoined) parts [2]. Regarding marketing mix ofculture heritage it can

be said that 'the key to success in the development of heritage products (whether these are in the heritage tourism sector or indeed any other) depends on the ability to match the product or service being offered (which is, ofcourse, based on an understanding ofcon-sumer wants or aspirations) with the benefits sought by the customer (these can be both tangible and intangible, i. e. a tangible benefit is the actual consumption of the product or service itself and an intangible benefit might be the status or other 'feelgood' factor that arises either during the research process, during consumption or following consumption, such as being 'environmentally friendly' in supporting organic foodstuffs). Ifpossible, the heritage marketer should be 'one step ahead' of the customer in terms of their needs, in particular to circumvent any potential problems that could arise in the heritage provision' [12, 130]. The conceptual model of conjoint analysis helps in this process because 'is quite straightforward; it postulates that the utility of a multi-attributed item can be decomposed into specific contributions ofeach attribute and possibly their interactions. The approach is easy to implement if the number of attributes is small. But, problems arise in most practical problems because of the large number ofpossible hypothetical alternatives for a given problem. In general, only a subset of possible alternatives is chosen for the study [1, 37].

4.2 Ethical issues

The main ethical issues regarding TripAdvisor derives from 'fake review concerns, growth in competition from Google and other players as well as low-entry barrier could restrict growth in TripAdvisor's user base [15]. However social media networking and online shopping has increased progressively in the last decades and the agreement ofTripAdvisor with Facebook has increased by 35% of TripAdvisor's new reviews, deriving from its Facebook connected members' [6, 196]. It has been previously studied that 'mostly men tend to share their views on TripAdvisor or, alternatively, men more than women state their gender when posting their reviews [6]. According to Lee et al. helpful reviewers tend to: 1) travel to many destinations;

2) be indistinguishable from other reviewers in age and gender; 3) actively post reviews; 4) disclose their age and gender information less than other reviewers; and 5) give destination hotels a lower review rating than other reviewers' [4]. Also previous studies on the role of social media in online travel information search has pointed out that 'certain keywords (e. g., nightlife and restaurants) are clearly more likely to generate more social media search results as compared to others (e. g., attractions). Furthermore, Xiang & Gretzel (2010) argue that virtual community websites are more closely tied to the ''core'' tourism businesses such as attractions, activities, and accommodations, while consumer review sites are related to shopping, hotels and restaurants, and, social networking, blogs, and photo/video sharing sites with events, nightlife, and parks [6]. Filieri et al. proposes five factors for building consumer trust towards consumer - generated media: a. source credibility, b. information quality, c. website quality, d. customer satisfaction, e. user experience with consumer generated media [...]. Trust towards a Consumer Generated Media website influences travel consumers' intentions to follow other users' recommendations and fosters positive word ofmouth. Findings also show that information quality predicts source credibility, customer satisfaction, and website quality' [16, 174-185]. Some of the factors or potentials that will influence TripAdvisor reviews in the future are: 1. Increasing investment in the mobile platform to leverage growth in mobile devices; 2. Tapping growth in social media; 3. International expansion to fuel global traffic. Among the potential threats are listed: 1) fake review concerns; 2) increasing competition; 3) low entry - barrier as an industry (TripAdvisor faces competition not only from existing players but also potential new entrants in the travel review market) [3]. With rich user-generated content, TripAdvisor has valuable monetization opportunities. Travel businesses can advertise on TripAdvisor's platform and benefit from its large audience and global reach. TripAdvisor derives most of its revenue from the sale of advertising, primarily through click-based advertising and to a lesser

extent, display-based advertising. The remainder of TripAdvisor's revenue is generated through a combination of subscription based offerings, content licensing, and its recently launched private sale site, SniqueAway. It also offers deals on top hotels at lucrative discounts. TripAdvisor has diversified its geographical mix in the past few years with the contribution of its US operations declining from 82% in 2008 to approximately 50% in 2015. Long-term revenue growth is expected to be driven by expanding traffic and user generated content [3]. 'Furthermore, a study on TripAdvisor and reviews' influence when choosing accommodation has already revealed that potential travellers consider these reviews accurate. Moreover, actively responsive businesses are viewed favourably by users, regardless of whether they are dealing with positive or negative feedback, as they appear to care about their customers' experiences [6, 190].

5. Methods

Prior research on consumer preferences stemmed mostly from face to face communication and a certain and given commercial contexts. 'Internet has led to changes in the nature of research, both in terms of challenging the assumptions that used to underpin market research (such as sampling theory) and in terms of opening up new possibilities, for example through the use of blog mining and online research communities' [7]. In the course of implementing conjoint measurement methods to applied business problems, such as those encountered in marketing, the emphasis on theoretical aspects of measurement has given way to the more pragmatic issues of design of studies and analysis of data [1, 3].

In this paper I have analysed 130 TripAdvisor reviews regarding Albania and its main destinations from the period 1 April 2016 to 31 October 2016. The process of conjoint analysis as a method has been divided in two main groups. The first phase includes the discovering of the main preferences of the visitors of the cultural heritage in Albania. I have started my study from the zero and basing it only in the TripAdvisor reviews and by comparing later

those data with the official Albanian statistics. Also the preferences will be grouped in different categories and those categories were subject to a questionnaire for visitors of cultural heritage in the second phase of the research. 'A significant advantage of the conjoint method has been the ability to answer various "what if" questions using market simulators; these simulators are based on the results of an analysis of conjoint data collected on hypothetical and real choice alternatives' [1, 8].

In the selected reviews I have determined four attributes that were repeated more frequently by the visitors and were related also with some features of the marketing mix components - product, price, place and period of time to visit Albania. These were the most salient attributes of the visitors writing reviews on TripAdvisor. The implications of these four attributes are quite clear from the data that were extracted and had an immediate impact on the demand and revenues of heritage tourism in Albania. The analysis will encompass also models of interactions. I based my models of interactions in the assumption that 'models that include interactions between brand and price might make sense in some situations [17, 5]. My first main interest was in marketing and promotion, however, it was difficult to measure 'promotion' in interaction with other attributes such as price, product, place or time. Since TripAdvisor is closely related to marketing and promotion, promotion as a category was everywhere, but most of the reviews:

- were asking practical information, (and/or);

- they were planning their visits and were not informed for what to expect; (and/or);

- it was their first time visit in Albania (and/or);

- they got the information mostly by internet.

For all these reasons it was difficult to study the

different values of promotion in their interaction with the values of other attributes. 'Choice alternatives may be described in terms of their components or attributes. For example, price is an attribute that influences choice of an automobile. Interest may be in several price points, or levels, such as $21,000,

$26,000, $31,000, $36,000, and $41,000. Other attributes might include brand name (with levels: Ford Taurus, Chevrolet Malibu, Mitsubishi Lancer, Volvo C30, Honda Accord); number of doors (two, four); size of engine (four, six, or eight cylinders); and type of transmission (manual five speed, automatic five speed, manual six speed, automatic six speed). Under certain conditions, it is possible to infer the partworth (or part utility) ofthe respective attribute levels by regressing information about product attributes on sales or market share. Such data are referred to as revealed preference (RP) data' [17]. Essentially, there are four types of conjoint methods: the traditional method (CA) that uses stated preference ratings; choice-based conjoint analysis (CBCA) that uses stated choices; adaptive conjoint analysis (ACA) developed in part to handle the issue oflarge numbers of attributes, and self-explicated conjoint analysis, which is a bottom-up method [1, 5]. The main conjoint analysis method used in this paper derives from the traditional full -profile conjoint analysis. 'Academics have suggested that the full profile approach is useful for measuring up to about six attributes [...]. I have chosen this method because the full-profile conjoint analysis may be used for paper-and-pencil studies and it can administered via computer. Also the full profile conjoint analysis may be used for computer assisted personal interviews (CAPI) and Internet surveys [2, 41]. In our days there are different software packages that analyse the data retrieved from the conjoint analyses directly as those published by the Sawtooth Software Company such as CVA, CBC etc. However I have analysed the results of this research based on the orthogonal method of SPSS.

5.1. Data collection

'The traditional conjoint analysis collects preferences for profiles of hypothetical products each described on the entire set of attributes selected for the conjoint study. These profiles are called full profiles' [1, 6]. In this paper I have decided upon different levels for the four attributes of the marketing mix system: product, price, promotion and place and I have added

also another attribute 'the period of time' as mentioned and analysed in the TripAdvisor reviews. I have chosen different values for each attribute. For example for price I have chosen nominal values such as: 'cheap', 'medium price', 'expensive' and 'price is not important' based on the reviews of the visitors or upcoming visitors ofAlbania and its cities.

a) (CH) Product - culture heritage product as analysed in the TripAdvisor reviews and their main repetitions resulted as below: Museums and art gal-

leries (2%), UNESCO cities (6%), Nature (1%), Ottoman Period (1%), Communist Past (2%), People, local food (9%), Saranda & Butrint was mentioned in the 4% of the analysed reviews and accommodation and infrastructure consistituted 2% of the CH product as mentioned in the TripAdvisor reviews. Most of the reviewers (73%) made no reference to the product of culture heritage and discussed about other topics such as price, promotion, place and period of time to visit Albania.

Figure 1. CH Product represented in TripAdvisor reviews

Another category which was mentioned very often in the TripAdvisor reviews regarding visitors or upcoming visitors visiting Albania and its cities was the 'price'. Price was mentioned in 48% of the reviews, more than product (27%) and promotion

(9%). 'Place' was mentioned in every review taken in consideration for the scope of this study. The low rate of promotion maybe was related to the fact that the mere posting in TripAdvisor can be considered as a kind of promotion and is tautological in itself.

Figure 2. Categorization of 'price' according to TripAdvisor reviews

Figure 3. Categorization of 'promotion' according to TripAdvisor reviews Table 1. - Categorization of place according to TripAdvisor reviews

Frequency Percent Valid Percent Cumulative Percent

South Riviera 31 23.8 23.8 23.8

Permet 1 .8 .8 24.6

Gjirokastra 4 3.1 3.1 27.7

Butrint 2 1.5 1.5 29.2

Vlore-Fier 7 5.4 5.4 34.6

Pogradec 1 .8 .8 35.4

-17,1; J Tirana 26 20.0 20.0 55.4

Valia North/Mountains 10 7.7 7.7 63.1

Durres 6 4.6 4.6 67.7

Shkoder 6 4.6 4.6 72.3

Berat 6 4.6 4.6 76.9

Albania 29 22.3 22.3 99.2

Korca 1 .8 .8 100.0

Total 130 100.0 100.0

Table 2. - Interactions between attributes regarding conjoint analysis

Product Price Place Period of Time

1) Museum, art galleries 2) Archaeology 3) Ottoman Period 4) Communist Period 5) Local Culture, Food, People 1) Cheap 2) Medium Price 3) Expensive 4) Price is not important 1) Southern Albania 2) Tirana 3) Northern Albania 4) Every part of Albania 1) January - March 2) April - June 3) July - September 4) October - December

It is common that when one concatenates levels of all attributes, the complete set of full profiles (or full factorial design) will in general be very large. A respondent will be unduly burdened when asked to provide preference judgments on all profiles [1]. In

this first phase of the conjoint analysis I tried to get a smaller set of values, however the stated preferences from the above combinations resulted through the orthogonal design of SPSS in 25, as they are represented in the table below:

Table 3.

Card Id Product Price Place Period Of Time

1 Local culture, people & food Expensive Southern Albania October - December

2 Museums, Art Galleries Expensive Southern Albania July - September

3 Archaeology Cheap Northern Albania October - December

4 Local culture, people & food Medium priced Every part of Albania July - September

5 Ottoman Period Expensive Northern Albania January - March

6 Museums, Art Galleries Medium priced Northern Albania April - June

7 Communist Period Expensive Tirana January - March

8 Communist Period Price is not important Every part of Albania January - March

9 Communist Period Medium priced Southern Albania October - December

10 Local culture, people & food Cheap Southern Albania January - March

11 Ottoman Period Medium priced Southern Albania January - March

12 Ottoman Period Cheap Northern Albania July - September

13 Ottoman Period Cheap Every part of Albania October - December

14 Archaeology Medium priced Tirana January - March

15 Museums, Art Galleries Cheap Every part of Albania January - March

16 Local culture, people & food Cheap Tirana April - June

17 Archaeology Cheap Southern Albania January - March

18 Communist Period Cheap Southern Albania April - June

19 Ottoman Period Cheap Tirana July - September

20 Archaeology Expensive Every part of Albania April - June

21 Archaeology Price is not important Southern Albania July - September

22 Museums, Art Galleries Cheap Southern Albania January - March

23 Museums, Art Galleries Price is not important Tirana October - December

24 Ottoman Period Price is not important Southern Albania April - June

25 Local culture, people & food Price is not important Northern Albania January - March

'The use of abstract alternatives in the form of concept profiles reduces cost and execution time by providing prospective decision makers with what is thought to be the essential information that will ultimately drive preference or choice. Constructing concept profiles following appropriate experimental designs ensures that relevant data are available for estimating partworths of attribute levels' [17, 2]. 'The traditional approach to CA also has an opportunity cost. In competitive markets, the success of a firm is influenced by both its own and its competitors' efforts. For example, a firm's market share is influenced not only by its own price but also by its competitors' prices, and the impact on market shares of a change in its own price depends on whether the change is matched by competitors. Traditional CA

procedures are suited to capturing the effects of the efforts of the firms. They are ill suited for capturing the effects of competitors' actions because traditional conjoint studies do not require respondents to make trade-offs between profiles, only between levels of attributes for a single profile [17, 7].

6. Results and analysis

From the 25 combinations that were retrieved by the orthogonal design of the SPSS I have eliminated the ones that are more improbable to occur:

1) Visiting Southern Albania by focusing mainly on local culture, people & food, with an expensive price, between October - December;

iНе можете найти то, что вам нужно? Попробуйте сервис подбора литературы.

2) Visiting Northern Albania by focusing on archaeology with a cheap price between October - December;

3) Visiting Northern Albania by focusing on the Ottoman Period with an expensive price between January and March;

4) Visiting Tirana by focusing in the communist period and history, with an expensive price, between January and March.

Still the number was too large to be represented in a survey. And thus were eliminated other combinations that were thought as less interesting for visitors:

5) Visiting Northern Albania by focusing on local culture, people & food, between January and March. Price is not important;

6) Visiting Tirana, by focusing on the archaeology, with a medium price between January and March;

7) Visiting every part of Albania by focusing on museums and art galleries with a cheap price between January and March;

8) Visiting every part of Albania, by focusing in the communist period between January and March. Price is not important;

9) Visiting Southern Albania with a medium price, and focusing in the communist period, between October and December;

10) Visiting Southern Albania by focusing on museums and art galleries, with a cheap price between January and March;

11) Visiting Southern Albania by focusing on local culture, people & food by paying a cheap price between January & March;

12) Visiting Tirana by focusing on museums and art galleries between October and December. Price is not important;

13) Visiting Southern Albania by focusing on the Ottoman Period, with a medium price between January & March;

14) Visiting Southern Albania by focusing on archaeology with a cheap price between January and March;

15) Visiting every part of Albania by focusing on the Ottoman Period, with a cheap price between October and December.

The other remaining conjoint analysis combinations were part of a survey with 75 foreign tourist in the period between March - April 2017. As the most quoted categories were those related to culture heritage and history in the period from March to September.

Table 6. - Results of survey with foreign tourists in Albania

2.5% Visiting Southern Albania by focussing on the Ottoman Period between April and June. Price is not important. Visiting Tirana by focussing on local culture, people & food with a cheap price between April & June. 5.6%

2% Visiting Southern Albania by focusing mainly on museums & art galleries, with an expensive price between July - September. Visiting every part of Albania by focussing on the archaeology, with an expensive price, between April and June. 5.4%

22,5% Visiting every part of Albania by focusing on local culture with a medium price, between July - September Visiting Southern Albania by focusing on archaeology between July and September. Price is not important. 17.4%

7.6% Visiting Northern Albania by focusing on the communist period, with a cheap price between July & September. Visiting Southern Albania by focusing on the communist period, with a cheap price between April and June. 11%

9% Visiting Northern Albania by focusing on museums and art galleries with a medium price in the period between April and June. Visiting Tirana, by focusing on the Ottoman Period, with a cheap price, between July and September. 17%

As a summary, it can be added that marketing plans stant monitoring and evaluation of segmentation bases need to be changed or modified to accommodate are highly important (daily) activities for the heritage macro and micro changes in the marketplace. 'Con- marketer and the research methods by which data are

collected must also be kept under review' [12, 81]. From the above data it can be derived that foreign visitors of Albania are more interested to travel from the period from March - September, like to have cheap or medium prices and have in interested in every part of Albania. Visitors interested in the archaeology are more interested in the Southern part of it.

7. Conclusions

In this paper I tried to shed light on the complex relations between market segmentation of culture heritage and market segmentation in Albania based on: 1) online reviews in TripAdvisor and; 2) a survey with 75 foreign visitors. The main research method was based on the full profile conjoint analysis in both survey designs. In the first phase of the research different attributes were identified based on the repetitions and main subject of reviews on TripAdvisor. From these were selected four attributes that were

similar to those of marketing mix: culture heritage product, price, place, promotion and period of time. These attributes were measured individually and in interaction with each other. SPSS program was helpful during the conj oint analysis by using the orthogonal design. Four different attributes (product, price, place and period of time) there were given different [1] values, that resulted in 25 different combinations. Since this number was too large, were taken in consideration only those categories that were more logical and were compatible with the official data. The final results derived from a survey with foreign tourist in Albania realized during the March - April 2017 resulted that visitors were more interested in to travel from the period from March - September, like to have cheap or medium prices and have in interests in every part of Albania and especially to its history, culture and archaeology.

References:

1. 2.

Rao V. R. Applied Conjoint Analysis. London: Springer, - 2014. - 37 p.

Orme B. K. Getting Started with Conjoint Analysis: Strategies for Product Design and Pricing Research. New York: Research Publishers LLC., - 2010. - 41 p.

Team. Here's Why We Believe TripAdvisor's User Base Will Continue To Climb. - 2013. Retrieved from: URL: https://www.forbes.com/sites/greatspeculations/2013/03/08/heres-why-we-believe-tripadvisors-user-base-will-continue-to-climb/#1e0994743cb2

Lee H. et al. Helpful reviewers in Tripadvisor, an online travel community // Journal of Travel & Tourism Marketing, - 2011. - 28 (7). - 683 p.

Trefis Team. Trip Advisor: What has changed. - 2016. Retrieved from: URL: https://www.trefis. com/stock/trip/model/trefis?easyAccessToken=PROVIDER_fe465c43de597290f0ce0344834824d 0129cfaef&from=widget: forecast

Kladou S., Mavragani E. Assessing destination image: An online marketing approach and the case of Trip Advisor // Journal of Destination Marketing & Management. - 2015. 4 (3). - 197 p. Poynter R. The handbook of online and social media research: Tools and techniques for market researchers. London: Wiley. 2010. - xiii.

Albanian Institute of Statististics, Statistikat afatshkurtra (Short-term statistics). - 2016. Tirana: Instat. Lonely Planet: URL: http://www.lonelyplanet.com/albania/internet-access

10. Eaton J., Roshi E. Chiseling away at a concrete legacy: Engaging with Communist-era heritage and memory in Albania // Journal of Field Archaeology. - 2014. - 39 (3). -318 p.

11. Hall D. Foreign tourism under socialism the Albanian "Stalinist" model // Annals of Tourism Research. -1984. - 11 (4). - P. 539-555.

12. Misiura Sh. Heritage Marketing. Oxford: Elsevier, -2006. - 130 p.

3.

4.

5.

6.

7.

8. 9.

13. Raghavarao D. et al. Choice-based conjoint analysis: models and designs. New York: Taylor & Francis, -2011. - 2 p.

14. Vasquez C. Complaints online: The case of TripAdvisor // Journal of Pragmatics. - 2011. - 1714 p.

15. Trefis Team. Here's Why We Believe TripAdvisor's User Base Will Continue To Climb. - 2013. Retrieved from: URL: https://www.forbes.com/sites/greatspeculations/2013/03/08/heres-why-we-believe-tri-padvisors-user-base-will-continue-to-climb/#1e0994743cb2

16. Filieri R. et al. Why do travelers trust TripAdvisor? Antecedents of trust towards consumer-generated media and its influence on recommendation adoption and word of mouth // Tourism Management. -2015. - 51. - P. 174-185.

17. Raghavarao D. et al. Choice-based conjoint analysis: models and designs. New York: Taylor & Francis, -2011. - 5 p.

i Надоели баннеры? Вы всегда можете отключить рекламу.