Maldives Hotels and Agents Relationships Factors Analysis


The research entitled ‘ANALYSING THE FACTORS THAT AFFECTS THE RELATIONSHIP BETWEEN AGENTS AND HOTELS IN MALDIVES’ is conducted with a major aim to analyse and fork out the various factors that affects the relationship between the agents and hotels operating in the Maldives tourism industry. The research has been conducted after carefully constructing the objectives, which will plays a huge role of significance in order to evaluate the actual outcome of the research. The literature associated with the topic of the research has been critically analysed within the desired sections, which states the fact that there are various elements that are needed to be evaluated during the build- up process of a business relationship. After conduction of the critical literature review, the researcher highlighted the various methods that are opted in order to successfully complete the research. The study is based on primary research and hence the data collection process was conducted on a sample size of 199 populations. The research design was an amalgamation of descriptive and explanatory research with hypothetical-deductive logic. The statistical software SPSS was primarily used and ultimately the data analysis package of MS excel was used to analyse the collected data. Furthermore, conclusions were highlighted after conducting the research and valuable and logical recommendations was put forward to overcome the issues that the research forked out.

Chapter 1: Introduction

Research Background

Business Relationship management is certain formal that helps to develop long- term bonding within two business partners or organizations, which ultimately provides both the parties with immense scope to excel in their overall trade process (Berling 2012). The tourism sector is one of those sectors that have flourished in the last epoch to a massive extent. Several nations have garbed the gigantic business opportunity within the tourism sector and have proved the worth of investing within the tourism industry (Tinsley 2012). Maldives is one of those places where the tourism sector has grown rapidly since its inception in the early 1970’s. The tourism has transformed the fiscal structure of the nation from a primarily finishing community to a world- class service industry within a small span of time (Pimpa 2008). However, as of all business industry, the tourism industry also has an immense amount of competition among several economies and organizations regarding the grabbing of the finest business opportunities present within this sector. Despite of China being a massive threat to all competitors of the tourism industry, the nation was unable to outperform any of its rivals within the industry, which clears out the confusion of any lack of trade opportunities within this sector (Griffith 2012).

Though majority of the times, China have outperformed Maldives regarding the revenue generation from the tourism industry, but still various surveys states the fact that the count of tourism visiting Maldives have increased massively over the last few years. Meanwhile, another massive fact have also been extracted by various researches, which states that the average stay of tourists in Maldives have decrease gigantically over the last few years, which have affected the business of the tourism sector to quiet some extent (Jackson 2009). Though a portion of losses that have aroused from less staying of tourist have been recovered from the fact that there has been a huge increase in the number of tourists visiting Maldives. Hence, the fact can be highlighted that the tourism sector of Maldives and its stakeholders have not been able to swallow the pie of profit that have aroused from the increased number of tourists visiting Maldives rather that has been balanced with the cut down in the staying days of tourists (Love, Staton and Rotman 2015).   

Relationship between the Hotels and agents of Maldives have flourished to a certain higher standard in the last few years, which have increased customer satisfaction and at same time have achieved customer loyalty as well. With a strong bonding of the two, the tourism sector has been exploited even more by the marketers, which have amplified the revenue generation of the entire industry as well. A survey in the year of 2012 showed that 61.79 % of tourists in Maldives have revisited the place within a small span of time and there was an increase of around 17.22 % of tourists each year, which highlights the fact that business opportunities within the tourism sector of Maldives will amplify itself to an even higher standard within the next 5 years (Ministry of Tourism 2016).  Therefore, it can be commented that in order to maintain the relationship both the parties have to deal with and maintain some basic elements such as trust, loyalty, commitment and reliability factors.

The year of 1999 bought in a huge boom for the tourism industry as the Maldives Tourism Act of 1999 has some amendments within its regulations and have started supporting the lease of land or islands for hotels and resorts (Mathias 2013). Apart from these the Act also supported various elements like how lease agreements should be drawn up between the concerned parties, terms and conditions of the lease of islands, the transfer and sales rights to third parties, taxation from tourists and tourists establishments (Mc Cormack 2011). Apart from an overall advantage for the sector, the implementation of these elements enhanced the relationships among the Hotels and Agents operating in the tourism industry of Maldives.

Rationale of the Research

Tourism sector is a certain division that have attracted the attention of various researchers in the past, which have also led them to conduct various researchers within this industry. The tourism sector of Maldives generates the majority of the revenues among all other sectors operating within the nation. Several researches have state the fact that the upcoming year of 2017 and 2018 will witness a massive growth of even more business opportunities within every tourism sector of all nations around the globe (Ministry of Tourism 2016).  The main stakeholders of the tourism industry are the Hotels, resorts, tourists, agents etc, which states the fact that a certain sort of collaboration, understanding and loyalty within the stakeholders will flourish the business operations to an even higher success level. The time span of 2001 to 2004 has experienced various issues within the agents and hotels which had affected the business operations of the industry as whole (Ministry of Tourism 2016). The sector which usually generates the highest revenue within the nation was unable to generate even standard revenues in the year of 2009 and 2010 despite of having massive business opportunities (Ministry of Tourism 2016). The sole reason behind this drawback was the various types of arguments and mismatches of decisions and demands that aroused within the agents and hotels relating to issues like trust factor, reliability, resources, commitment etc. The major rationale behind this research is to extract the factors and elements that affect the relationship between the two of the major stakeholders of the Maldives tourism industry (Ministry of Tourism 2016).

Apart from that the research will also analyse the extra business opportunity that might be discovered by the agents and hotels if they collaborate with each other and maintain a healthy business relationship. The issue is regarding the arguments within the business relationship of the hotels and agents in Maldives, which have can have a massive negative effect on the tourism industry in the upcoming years.

Inflation has loomed over every industry and the tourism sector is not an exception, which states the fact that losing any sort of opportunity of business no less than losing revenues intentionally. Therefore, the importance of the study is massive in the present time, as various researchers and surveys have confirmed the fact that the tourism industry will experience a huge rise in the number of tourists visiting various places. Mysen, Svensson and Hagevold (2012), opines that Quality service and fulfilling of commitment are some of the major components that should always be satisfied by the marketers of a service industry. Meanwhile, Sheth and Parvatiyar (2015), states that revenue generation within any industry majorly depends on the quality of the manpower that the management of the firm have hired in the concerned positions. Hence, an argument can be aroused from these two statements, which states that there has been a huge gap of opinion within the two authors. However, the research will analyse both the elements which will enable us to ensure the actual pivotal elements of the tourism industry. The derived result can also be relied upon as majority of the research is extracted from practical implications and underpinned theories’ of well renowned authors.

The research will shed immense light on the various factors that plays a massive role of significance in retaining a balanced and handsome relationship within the hotels and agents of the tourism industry of Maldives (Petrof 2007). Moreover, the research will also analyse the massive effect of change that friendly collaboration of the hotels and agents can bring in within the tourism industry of the nation. Therefore, the research will analyse all these elements and at the same time the expected outcome will remove all sort of confusions regarding the actual elements that have constructed a certain barrier among the relationship of the hotels and agents of the sector.

Research Aims and Objectives

The chief aim of the research is to fork out and analyse the factors that affect the relationship both in a positive and negative aspect among the Hotels and Agents in operating in the tourism sector of Maldives. The objectives of the research are listed below:

  • To analyse the role played by trust and reliability in retaining the relation between the Hotels and Agents
  • To examine the role of successful commitment played in retaining the relation between the Hotels and Agents
  • To determine the importance of communication between hotels and agents
  • To monitor the role played by loyalty in retaining the relation between the Hotels and Agents
  • To fork out the reason behind agent/hotels maintaining resource commitment to sustain relationship and business for both parties

Research Structure

The research consists of five chapters, and each of these chapters has its own significance, which will satisfy the major aims and objectives of the research.

 The first chapter is entitled as “Introduction”, which will provide the reader with an overview of the entire research and at the same time will also highlight the major aims and objectives behind conduction of the research. Moreover, this chapter will also provide an overview of the various pivotal elements that the researcher has used and the questions are aimed to answer after conducting the research successfully.

The second chapter will elaborate the literature associated with the topic of the research, which will enable the researcher to understand the gap within the literature and the collected real- life data. Moreover, a conceptual framework will be constructed which will enable the reader to understand the entire concept of the research in a visual manner.

The third chapter will highlight and uphold the methodology used to complete the research. The type of research methods used will be elaborated within the research along with the sample size and will list down the software used to analyse the collected data.

The fourth chapter will analyse the data and descriptive discussion of the extraction will be put forward, which will enable the researcher to understand the current status of the research and at the same time will also enable to understand the current situation of the tourism sector of Maldives. Apart from this, analysing of the data will also enable the researcher to meet the research aims and objectives, meanwhile understanding the factors that affect the relationship between the Hotels and agents in Maldives.

The last and the fifth chapter will discuss a bit on the findings from the previous chapter and eventually will close by providing necessary recommendations, along with scope of future research in any identical domain.

Chapter 2: Literature Review

2.0. Introduction

Maldives is a southern strip that is 500 kilometres from India and Sri Lank that has low lying coral islands across the equator in the Indian Ocean. It provides a glimpse of a beautiful string of striking balmy paradise. If considered the lagoons and sun-kissed beach, it gives the exotic marine life existing in the palm-tasselled island. According to famous Moroccan traveller, Ibn Battuta, it is “one of the wonders of the world” (Waines 2012).

However, the three geographical realities that beckon the island are the three S’s- Sun, Sea and Sand. Maldives is known for its luxurious spot for lazing around, relaxing and enjoying the colourful panorama presented by nature. After considering Maldives beauty, many tourists come in a flock to get the comfort and warmth provided by the hospitality industry in Maldives in resorts, hotels and guesthouses, which makes Maldives as one of the vibrant destination for holidaying (Kundur 2012).

Conceptual Framework

Conceptual Framework

Source: Created by author

2.1 Hotel Industry

Maldives is one of the countries rich in hotel industries. The global community of the tourism industry in Maldives show fruition in an international advent of tourism since 1950 and has forecasted to increase to a 1.6 billion and the receipts generated will internationally increase to US 2 trillion dollars by 2020. However, these figures by WTO are assumed to be highest in the global hotel industry and have asserted that the hotel industry has kept in mind all factors relating to human society. However, if Maldives is determined from any dimension of the gross domestic product, capital investments, human resource management, sustainability and other factors like trust, loyalty, resources, etc. has created to realize the benefits that the industry can possess and are indispensable (Shakeela and Cooper 2009).

2.2 Characteristics of Accommodation Industry

The accommodation industry varies on the four principles outlined By Loycker (2013) mainly Intangibility, inseparability, variability and perishability.

Intangibility is referred to the basis of services that are offered by the accommodation industry. Every product is unique in its characteristics such that the experience gained from each service is fundamentally different from other. However, the tourists who are willing to buy the services will look for the information of the individual package in advance to reduce the uncertainty in the long run (Jaume 2013).

Inseparability mentions the relationship that is made between the customer and employee. However, according to Loycker (2013), the customer is also an essential part of the product. With the help of an example inseparability can be explained- Suppose food in a restaurant is outstanding but the attitude with which the waiter offers service is not good. As a result, the customer will not be satisfied with the experience. However, there is a requirement to understand the cultural differences that influence the relationship.

Variability can be measured regarding the services offered in the peak periods and the non-peak periods referring to its quality and control. However, with proper staff training the occurrence of variation in the client’s behaviour can be reduced (Blancas et al. 2010)

Perish ability factor can be determined regarding intangibility and fleeting commodity. The accommodating industry does not offer benefits that can be stored because if one room is left unsold for the night, it will not add to the inventory because the revenue generated from that one room is lost and cannot be regained. Hence, the services/products offered by accommodating industry are unpreserved (Riley 2014).

The accommodation product can be characterized based on accessibility, facilities provided, service level regarding quality and price, image that advertising builds and the ability to differentiate the product from other products (Page 2014).

3.0. Definitions of B2B relationship

Claycomb and Martin (2002), states B2B relationship is the acronym stands for Business-to-Business relationship that ensure creating as well as sustaining the long-term relationship status that delivers the key target for establishing the business activities successfully. Be it any company, it often pays more attention to the successful relationships among the business partners for generating mutual benefit (Claycomb and Martin, 2002).

Garbarino and Johnson (1999), mentioned Business-to-Business relationship also illustrated that organizational relationship management between business partners and its high position in the business network have significant role in giving solution to the critical tasks available on which the survival of any business stands and/or falls (Garbarino and Johnson, 1999).

Mr. Anderson and Narus (2014), states B2B relationship can offer a stand-out performance to the business by relying on their relationships with customers, suppliers, partners, shareholders, trade associations and so on. Many businesses nowadays relocate their emphasis from discrete transactions to shape long-term and mutually profitable business exchange relationships (Anderson, Narus and Wouters, 2014).

B2B relationships can also be described as the long-term process established in the businesses where many companies structure and extensive and strong, economic, social, technical and service ties over each passing day, with the intention to lessen the total cradles or/and rising value for accomplishing mutual benefits.

Bagdoniene and Zilione (2009), points out Business-to-Business or B2B relationship as the process in which, one business makes the commercial transactions with another business. The process generally happens when a business is outsourcing its products and services for their successful production process (Bagdoniene and Zilione, 2009). It also emerges when one business demands the services of another on behalf of operational reasons and the business when opt for reselling its services and goods manufactured by others.

4.0. Tourism in Maldives

The tourism is Maldives is growing in a way that uninhabited islands are changed into resorts taking into consideration the concept of “one island one resort” for luxury vacations. However, there are mainly for the type of lodgings that the tourists prefer to be in namely tourist resorts, guesthouses, hotels for tourists and live board vessels for safari. If considered according to the data given by MoTAC, resorts registered were 105 with total bed occupancy of 22,889 and if analysed on hotels. The hotels decreased from 20 to 19 as one hotel withdraw its operations with total bed occupancy of 1627 in 2012 (, 2012).

The budget accommodation that accounts for guest houses in operation. The guesthouses are developed in local islands for continuous access to the beach and the nature of the Maldives. However, this type of lodgings was previously in Malè (capital city of Maldives). The guesthouses register a considerable amount of bed occupancy but according to the MoTAC report, this type of lodging is increasing within the industry (Peterson 2013).

The other type of lodging that draws tourist attention is safari vessels in which the tourists experience an onboard holiday with adventurous activities like snorkelling, diving, wave surfing, and types of available game fishing. Nevertheless, these safari vessels cruise around the islands. Therefore, in 2012 Maldives had 154 safari vessels (Shakeela et al. 2014).

4.1. Tourism Market in Maldives

The tourism market can be analysed with the help of Ministry of Tourism in Maldives (MoTAC). According to MoTAC, the number of tourists in 1972 amount for 1,097 tourists, this grew to 1.1 million in 2013. However, until the 1990s the major tourist arrivals were from Europe but in 2000s Europe’s market share decreased, and now the major visitors were from Asia particularly from Mainland China succeeding the fast-paced economic growth. However in 2013, the visitors crossed the 1.1 million mark which was largely attributed because of new air routes to Maldives and various tourist campaigns (Sorgiovanni and Tan 2014).

4.2. Seasonality in Tourism in Maldives

The changes in market composition have recently lowered the strong seasonality of the industry. Peak and non-peak periods influence the tourism industry. The seasonality factor is affected by the change in dominance of the markets from European market to the Chinese market. However, before the 2000s the peak periods coincided with the winter months from December to February and non-peak periods accounted for months May, June and July (Goodall and Ashworth 2013). As evident with the expansion of Chinese market that has softened the seasonality of the tourism industry. These changes have been accounted for small deviations in the trend that have been statistically significant. The trend has depleted in the months of August and October as maximum Italians used to take vacations in the 1990s but today Italians share of tourists have decreased amongst the total tourists. As a result, the seasonal factor has been strengthened in the last five years due to the incursion of Chinese tourists in the month of October. Subsequently, the variability observed in the tourist arrivals for the Chinese tourists is greater than the European tourists.  This underlines that though Europeans have established their seasonality tourism it does not undermine the arrival trends of the Chinese, which comparatively serves as a new source of market for the Maldives (Adam et al. 2014).

5.0. Measuring the hotel-agent relationship nature

Relationship success: The agents are the successful people with whom hotel business can see its growth and popularity in the marketplace. The effort and valuable time spend on creating and maintaining the B2B relationship with them is worthwhile for the business.

Quality communication channel: The quality of the communication channel should be strong between hotels and agents so that hotels can establish a back-and-forth communication with the agents.

Exchange of information: Sharing of information between hotels and agents will be beneficial for both as one’s information might help the other party. Hotels offer legitimate information to agents for selling their products and services (Konhäuser, 2008).

Relationship commitment: Trust is the vital component for establishing a never-ending relationship commitment status in any business. Strong sense of loyalty and maximum effort is also needed for creating and maintaining a long-term commitment towards the B2B relationship.

Conflict- resolution methodologies: In every commercial business-to-business relationship, conflicts are occurring and it is vital to resolve them. Therefore, persuasive attempts by either party, joint problem solving capability and smoothing over the problems are the worthy methodologies available in the business marketing world that can absolutely resolve the conflicts present in between hotels and agents.

In the relationship marketing field, it is understood that B2B relationship business is the best among other marketing mix concepts as in this environ few customers are responsible for making huge money transfers (Peterkin, 2014).

Six famous relationship variables available in the business marketing environment that are influencing the long-term B2B relationship and those are:

  • Trust (Pimpa 2009)
  • Reliability
  • Communication
  • Commitment
  • Resources
  • Loyalty

6.0. Assessment of External Factors

6.1. Climate Change Risks

The climate changes affect the feasibility and profitability of tourism industry directly and indirectly. However, climate plays an essential role in choosing a destination. However, climate can result in extreme situations of health and safety of tourists and the reputation of the country. Maldives is facing huge risks that can impact the tourist count. The beach erosion, the water availability, physical damage to property, warmer sea temperatures and the supply chains that are sporadic in nature are the key climatic factors. However, Maldives is experiencing a rise in sea level from 0.19 to 0.58 m in the twenty-first century. The presence of geographical variation in non-uniform temperature is affected by the changes in sea level. This change has also influenced the island tectonics and postglacial isostatic adjustment.

According to IPCC, the actual levels will vary and depend especially on the degree of melting glaciers in Greenland (Carlsen and Butler 2011).

6.1.1. Precipitation and Temperature

Maldives has a tropical monsoon climate, which is subject to increase in extreme rainfall around the year. However, the projections have showed an increase in daily rainfall and consecutive five-day event of rainfall due to climatic changes. The projected temperature depicts increased temperature in the northern portions of the country. The elevated temperature is affecting the marine biodiversity and fisheries (, 2015).

6.2. Non-Climate Change Risks

6.2.1 Land Use and Erosion

Maldives has a scarcity of land, and unused land is extended to small islands for accommodation purposes. Consequently, if population increases, increase pressure on land will increase which will result in overcrowding, degradation of coral reefs, groundwater pollution, deforestation and soil erosion. However, human interventions will furthermore accelerate soil erosion and cause loss of land disrupting the adventurous activities due to rise in sedimentation in the sea. Nevertheless, Maldives has recently used the policy of land reclamation (Sovacool 2012).

6.2.2 Supply of Freshwater

The freshwater is scarce and depleting because of over-extraction of aquifers that is not only affecting the quantity of water but also affecting the quality of water. In 2012. 58 islands reported the problem of water shortages. Today, Maldives is using rainwater harvesting in private and community tanks. Despite the fact that, the dependence on rainwater is increasing the helplessness in the dry periods (Bailey et al. 2014).

6.2.3 Biodiversity Loss

Tourism in Maldives is a hub of rich marine and coastal diversity, waters and sandy beaches that add economic value. The biodiversity in Maldives is experiencing stress from reclamation, beach sustenance activities, diving and reparation from scouring. However, some tourism operators permit an illegal sale of shells and jaws and night fishing activities, which are affecting the marine environment (, 2015).

6.2.4 Waste Management

The generation of waste is increasing due to more tourists visiting Maldives. The four types of waste that are rising are food waste, garden waste, residual waste and recyclable materials. These wastes are resulting in dumping in the sea and increase in greenhouse effect that is affecting the difficulty for live aboard vessels to get rid of waste (Mohee et al. 2015).

7.0. Six independent variables

Trust: Trust is the crucial factor that is described by many models highlighting the relationship marketing in a B2B relationship. There are lots of varied definitions about trust but most of them would agree that trust is the confidence level present in between parties defining that other party is trustworthy. By examining the earlier literatures, it can be stated that trust can be fabricate in three ways remarkably. Mr. Svensson says that, trust can be build with the help of three key elements those are honour, dependable and reliable that the business should demonstrate (Räikkönen, 2014). The businesses have to act according to the partnering business’s best interest. Apart from that, the business must work on their fairness reputation. In 1992, Sako divided the category of trust in three different parts, goodwill trust, competency trust and contractual trust. According to business point of view trust can be described as the organizational belief that states another business perform remarkable actions and endeavours that in turn generates positive end-results for the organization. But this could lead the company’s strength to do a trusting action or/and response (Räikkönen, 2014).  

H1: Trust has a huge positive influence towards in retaining a good relationship between Hotels and Agents

Reliability: Claycomb and Martin (2002) defines reliability as the key to have a taste of successful business environment. In hotel business, hotel owners should have to be reliable on their agents and vice versa for creating and maintaining a long-lasting B2B business environment. Without having reliability upon each other, a business will only see the down fall (Claycomb and Martin, 2002). Therefore, it is one of the key elements that influence the B2B relationship to sustain in the market stupendously. Bigger the reliability attribute the stronger will be your B2B relationship. In hospitality sector, hotels should find the reliable agents to market their business see the beyond compare business growth. 

H2: Reliability has a huge positive influence towards in retaining a good relationship between Hotels and Agents in Maldives

Communication: Räikkönen (2014), states that the communication channel would have greater influence in creating and maintaining the business-to-business relationship. It is because of the fact that if the communication fails to explain what your business can offer or what it is doing in the marketplace, then it will lessen the visibility of your business (Räikkönen, 2014). Therefore, it is a key aspect that businesses should adapt precisely. In hotel business, the agents do the work to maintain the communication channel clear on behalf of your business so that more and more customers will get familiar with your products and services.

Failing in creating or maintaining this attribute could hamper a lot to your hotel business as customers will not get anything what you are trying to say of making every effort to visualize them. It is believed that the depth of the business-to-business relationship is based on the importance of communication through which information is being shared. In hotel business, establishing a secure communication with the agents for sharing the sensitive information of the hotel and other important organizational features will ensure the business commitment and trust and conversely it will give your business some of the trusted agents to spread your business tremendously (Johansson Nilsson and Thulin, 2005).

H3: Communication is massively pivotal in retaining a good relationship between Hotels and Agentsin Maldives

Commitment: The desirable outcome that is available in the relationship marketing is the commitment. The commitment in business relationship marketing is acting just as the commitment exists in the marriage ceremony. Peterkin have defined commitment in business-to-business relationship as an incomplete relationship that works between two or more parties which is important to permit maximum efforts in maintaining B2B relationship (Peterkin, 2014). On the contrary, Johansson, Nilsson and Thulin (2005) states commitment as the virtual thing in business atmosphere that captures the perceived continuity as well as growth present in a business relationship established between two or more parties (Johansson Nilsson and Thulin, 2005). Commitment is significant in order for the company to grow and prosper to put effort into the business relationship and to demonstrate the goodwill of the other company.  

H4: Fulfilling the committed commitments are massively necessary for both parties (Hotels and Agents) to retain a good relationship among themselves

Resources: No doubt that the resources have also an essential role to play in B2B relationship. According to Bagdoniene and Zilione (2009), the primary objective of the business marketing is to be a trusted resource that the customers’ always carved for during their research. It will also give your users an ample set of information based on your customer’s areas of interest (Bagdoniene and Zilione, 2009). If you are running a hotel business, then the areas your customers are concerned about might be hotels, its facilities, amenities, services, transportation facility, and budget-friendliness and so on. By depending on these areas figuring out the ways to make it more precise so that your customers’ search for the resources will not give them dissatisfactory results will be the wisest choice for your business.   

H5: Maintaining resource commitment are gigantically pivotal to sustain relationship as well as business among Hotels and Agentsin Maldives

Loyalty: Loyalty is granted as the degree to which your potential customers will exhibit the repeated behaviour for purchasing products and services from you. Regardless, it will help them to possess an optimistic attitudinal character towards the service provider and assist them to think about the service provider when a need of the product and service comes up. Loyal customers will help the business to generate a steady stream of revenue by keeping up to venture the journey with the brand or supplier. It defines that the business-to-business customer loyalty is coming attached with the organizational change, trust, satisfaction, relationship quality, switching costs and purchase development (Gurcaylilar, Yenidogan and Windspergerc, 2011). The higher the quality of such relationship, the more flawlessly your business sales and help you as well as your business to grow in the international market arena. Loyalty is the thing available in the marketing concept that can’t be purchased as it has to be earned through effective business relationships.

(Source: Athanassopoulou 2009)

H6: Hotels being loyal to the agents and the vice – versa plays a massive role in sustaining their relationship for the long- term

8.0 Effects on tourism due to External factors

8.1. Loss in Tourism Expenditure

Maldives may experience a change in tourist preferences due to the effect of climate change because of the surrounding uncertainties that may or may not affect due to climate change and the distribution and severity that might affect Maldives on cut back decision on challenging tourist destinations (Eugenio-Martin and Campos-Soria 2014).

8.2. Loss in Retention of Tourist Satisfaction

The tourist satisfaction is disrupted because of the acidification of the coral reefs that has risen due to greenhouse gases and is affecting temperature. The tourist may not experience satisfaction from adventurous activities and may result in the loss of tourism revenues (GhulamRabbany et al. 2013).

8.3. Debate arising from owners of safari boat and foreign booking agents and the surfers

The growing debate in the two groups is heatedly opposed to the development of last undeveloped island of Maldives. However, this is impacting the decline of safari boat industry if a resort replaces the island. There is a need for proper decision vesting in favour of surfers who need a place for adventurous activities. This may lead to paradoxical nature in comparing the economic, social and political concerns (Ponting 2014).

8.4. Diabolical Nature of Politics

The inconsistencies in the human behaviour pave the path for a gap in dream and reality. However, nature is termed diabolical because the depiction of environmental concerns is based on the consumer and voting decisions and fixations of political agendas according to political survival (Hughes et al. 2015).

9.0. Critical Review

For better understanding of the B2B relationship between the hotels and agents, many literatures have given verdicts that are critically reviewed under this section. However, how the B2B relationship occurs, how hotels and agents are getting benefitted through this relationship, what will be the advantage of B2B relationship, use of internet sites in B2B relationship, hotel-agent relationship measurement and management are summarized hereafter. Therefore, this critical review will further give recommendation to the business activities.  

In the hotel business, agents are acting as an integral part committing to deliver the comfortable, memorable, convenient and economical journey to the customers. In fact, we can say that the agents are the bunch of un-coordinated people who lend a helping hand to accomplish the coordinate results. In the hospitality industry, agents are offering a virtual link to the customers thorough which they can fulfil their desire to serve the clients in a convenient way. Buhalis (2000), says that a good agent can act like a personal counsellor who has ample knowledge regarding the journey and the demands of the intending customers. Reciprocal success established in B2B selling frequently hang on to start and maintain a sound relationship to measure the benefits and costs (Buhalis, 2000). It facilitates business partners to create more value and to do more while focusing on the core competencies of the business and letting others to do the things that they can do better. As a complex phenomenon, business-to-business relationships have multi-dimensional characteristics such as value, functions, time structure, substance and process.

Johansson Nilsson and Thulin (2005), states that even though the advent of internet sites allows customers to book a hotel directly for their staying purpose, agents’ remains as a significant part of most hotels’ marketing mix (Johansson Nilsson and Thulin, 2005). The importance can be divided into following three reasons:

They are very close to the hotel’s customers and habitually play an important role in identifying the type of leisure and travel services that clients purchase.

Though, agents are not generating any computerized systems for reservations, they connect with the hotels and with the internet to have full access to the information about the services and products available via tourist suppliers. Thus, they are the important players in broadening the use of new-techs including the internet and computerized reservation systems.

The internet and computerized reservation systems provide outstanding choices to the agents for packaging the flexibility of holiday trips based on the particular preferences and demands of each individual client.

10.0. Hypothesis

  • H1: Trust have a huge positive  influence towards in retaining a good relationship between Hotels and Agents
  • H2: Reliability have a huge positive  influence towards in retaining a good relationship between Hotels and Agentsin Maldives
  • H3: Communication is massively pivotal in retaining a good relationship between Hotels and Agentsin Maldives
  • H4: Fulfilling the committed commitments are massively necessary for both parties (Hotels and Agents) to retain a good relationship among themselves
  • H5: Maintaining resource commitment are gigantically pivotal to sustain relationship as well as business among Hotels and Agentsin Maldives
  • H6: Hotels being loyal to the agents and the vice – versa plays a massive role in sustaining their relationship for the long- term

The business-to-business relationships are not only a complex phenomenon but also are multidimensional. The business endeavours are depending upon their B2B relationships with suppliers, partners, customers and employees (Proenasa and Castro 2006). Success story of B2B relationship will assist the business as well as agents to create mutual benefit and/or could help them in creating greater profitability and increasing value as well. The key role in creating and maintaining the business-to-business relationships are supremely carried out by several relationship variables those are outlined above (Claycomb and Martin, 2002). The examination of scientific literatures reveals that successive B2B relationship variables associate with business-to-business relationships in order to provide better visibility to the business and great profitability as well. Another thing about these variables is that they can’t act separately without the absence of one as they are dependent on one another.   

In the hospitality industry, establishing, creating and maintaining the business-to-business relationship is vital between hotels and agents as they are directly proportional to one another for doing business in the contemporary world (Konhäuser, 2008). One can’t leave another and make its sole journey successful; therefore, create the matchless and unique B2B relationship to grow mutually and earn maximum profit out of your hotel business.

Chapter 3: Research Methodology and Design

This chapter presents the method and the study to analyse the relationship between Hotels and Agents in Maldives on independent variables of trust, commitment, reliability, communication, commitment, resources and loyalty. The purpose of this chapter is on the techniques applied in choosing a large sample to collect data and obtain the answers to the proposed research questions while explaining the step-by-step procedure on the overview of gathered and analysed results (Johannesson and Perjons 2014).

3.1 Research Paradigm

A research paradigm is a framework that executes how the research needs to be carried out based on the research philosophies guided by people’s perceptions of the world and the knowledge’s nature. However, the ideas have changed about reality, and some new research paradigms have emerged as a reaction to the insufficiencies of the previous paradigms.  According to Kuhn in 1962 there has been only one research paradigm as “scientific achievements” and today the reference is made to the natural or social sciences (Collis and Hussey 2013).

However, two philosophical extents can distinguish research paradigms. They are significantly ontology and epistemology. The ontology assumption explains the nature of reality whereas the epistemological assumption measures the valid constitution of the knowledge. Nonetheless, epistemological deals with interpretivism for qualitative research strategies and positivism for quantitative research strategies. On the contrary, ontological assumptions deal with constructivism for qualitative (intensive) research strategies and objectivism for quantitative (extensive) research strategies (Bahari 2012).

The ontological assumption is concerned with constructivism that deals with knowledge that is indeterminate and adds meaning to the social phenomenon. The concept is also related to postmodernism. The objectivism deals with the knowledge that is agreed on, and the meaning of social phenomenon is independent of the social factors giving the tangible reality of its own (Bryman and Bell 2015).

consideration with natural science relates to positivism and the contrast to interpretivism. Hence, all philosophical assumptions can be differentiated based on positivism and interpretivism. The five philosophical assumptions can be differentiated on two main paradigms that are given in the table below.

Research Paradigm

  Positivism (Realism) Interpretivism
Ontological Assumption Reality is objective Reality is subjective
Only one reality (fact) Reality is based on the projection of imagination (Wangombe 2013)
Epistemological Assumption Quantitative Research Strategies (Objective) Qualitative Research Strategies (Subjective)
Disconnected and further interaction with phenomenon (Collis and Hussey 2013) Interaction with phenomenon
Rhetorical Assumption Passive voice and extensive set of words and definitions Active voice and qualitative set of former and limited definitions
Axiological Assumption Value free and unbiased results Value-laden and biased results
Methodological Assumption Deductive approach strategy Inductive approach strategy
Cause and effect relationship Relationship of topics within the context
Generalizations Patterns and Theories
Accurate results through reliability and validity Accurate findings through reliability and verification

However, positivism is the application that advocates the natural science to study the social reality whereas interpretivism is the positivist orthodoxy that promotes the natural science to seize the subjective knowledge of the social reality (Bryman and Bell 2015).

The both paradigms are similar to an extent because both use research questions and qualitative/quantitative data, use various techniques to review or reduce the research data, apply different means to analyze the data and lastly draw conclusions from the research (Zikmund et al. 2012)

However, in this research, positivist research paradigm is followed because of following reasons:

  • A large sample is considered of 200 observations;
  • The sample is set on an artificial location;
  • The data is quantitative in nature and the results are precise and objective in nature giving the relationship of each independent variable with the dependent variable;
  • A total of six hypothesis are generated following a deductive reasoning strategy;
  • However, the results are generalised from the sample to the population as a whole;
  • The results generated are produced with high reliability.

3.2 Research Design

A research design provides the framework for the analysis of the data collected. The choice of research design reflects not only the decisions about the priority but also the range to an extent the research process needs to be followed. A research design highlights the importance attached to the relationship between the variables, the use of large sample as a part of the investigation, understanding the behaviour in the definite social context and positive reception over time for interconnections of the social phenomenon (Bryman and Bell 2015).

However, the design research methodology is associated with research paradigms. The positivist research paradigm follows a research design that is experimental in nature, survey bound concerning primary or secondary data and supports cross-sectional and longitudinal studies (Collis and Hussey 2013).

The research design can be explained in two contexts.

  • Descriptive Research (The accuracy of the research- How?)

Descriptive research can be concrete or abstract and can be related to finding the relationship between the phenomena of the population. Hence, it cannot fit in any one methodology of qualitative or quantitative rather it can utilize both strategies. Moreover, this kind of research is efficient in uncovering new facts and meanings. The basic purpose outlined is to observe, describe and document (Creswell 2013).

  • Explanatory Research (The reason of the research- Why?)

Explanatory research looks the context of the reason for the nature of relationships. This research provides hypothesis testing in answering the specific research questions in the study. However, according to Zikmnd et al. (2012), the extent of the research establishes the research methodology.

  • Exploratory Research

Exploratory research can be used for discovering new ideas, growing knowledge of the phenomena to gain from new insights. Through this research, the researcher can test the possibility of extensive research and the diverse approach used in the study. However, this research is broad yet oddly provides distinct answers to the particular research ( 2015).

The research design can be summarised in the table given below.

Summary of Research Design

  Exploration Explanatory Descriptive
Aim To identify the factors that are relevant to the research Analytical in nature that provides connection between the factors It provides accurate and valid results of the factors
Degree of Problem Major variables are not identified Major variables, and meaningful relationships are identified Major variables are identified  
Structure Lacks formal structure Structured More structured than exploratory research
Questions answered What? (objective) Why? (Reason) How? (possibility/accuracy)

 Source: (van Wyk 2012)

The planned research is the amalgamation of descriptive and explanatory research with hypothetico-deductive logic. The research develops a strategy of inquiry in which correlational studies are conducted in a natural setting such that no new insight is modified in the phenomena. These studies are designed to establish the effect of one extent of the phenomenon to another extent that emphasizes the relationship of variability in one concept by using the information from one or more variables. However, this may generate the association testing theories that are designed to test relationships between variables/factors and hence give valid results (Creswell 2013). The hypothetico-deductive logic is followed because the research is intended on the theoretical framework made to develop an idea and certain hypotheses are laid down. The evidence is collected using data collection methods and with the help of findings the discussion is carried out on the theory generated the literature review (van Wyk 2012). This research follows the particular line up to check the efficiency of both the research.

  • The researcher can examine the relationship between independent and dependent variables and the correlational studies help in determining the relationship between the independent variables.
  • It allows the testing of the past theories developed on hotel and agents that could be executed in Maldives.
  • It allows analyzing the market trends of the tourism market and the customer retention problem in Maldives accommodation industry.
  • It also identifies the reasons, cause and effect relationship due to the seasonality and different internal factors like trust, commitment and external factors like climate and politics in the tourism industry that affects hotels and agents in Maldives.
  • The current situation is explained in Maldives
  • The researcher uses various forms of data in analyzing the relationship between hotels and agents.
  • However, with the help of independent variables, the researcher provides the knowledge of the theory that is further used to make significant decisions.

3.3 Research Methods

After identifying the research design, it is now important to communicate information about the important features of the study that can differentiate from qualitative, quantitative and mixed methods (Harwell 2011).  However, research methods can be broadly classified into two research methods.

3.3.1 Qualitative and Quantitative Research Method

Quantitative Method

This method is used to quantify data and generalize the results from the sample of observations from the population of interest. This method has its key objectives to measure the incidence of the opinions and view of the chosen sample (MacDonald and Headlam 2009). However, this research uses a large scale of the sample used under the methods of questionnaires or surveys. This type of method reaches to a large number of people, but the contact with the people is lower than the qualitative method, which is more time consuming (Dawson 2009).

Qualitative Method

The quantitative data is a game of numbers, but a lot of information cannot be condensed to numbers. The feelings of people, judgment, comfort, emotions, beliefs and ideas are only expressed in words and cannot be manipulated mathematically. Hence, it requires quite various analytical methods that can be used to devise a person’s behavior (Walliman 2010).

It thereby measures the precise meaning of words with interrelationships between the variables because they are real and detectable even they are complex to record and measure (MacDonald and Headlam 2009).

The comparison of the qualitative and quantitative methods is described in the table below.

Quantitative and Qualitative Research

  Quantitative Research Qualitative Research
Aim Attempt to present results in a numerical form with an aim to elucidate what is observed Attempt to give a detailed and complete description to what is observed
Tools Surveys and Questionnaires Participant observation, in – depth interviews, or an in -depth analysis of a single case (Ezzat, 2015).
Purpose Causation, Generalization and Prediction of the relationships Discovery, adding meanings and interpretation, understanding and contextualization perspectives
Data Collection Structured Not Structured
Analysis Statistical analysis (Numbers) Interpretive and Narrative (Ideas and Words)
Sample Large  number that represents the sample population Small sample that is non-representative and are selected based on the experience
Role of the researcher Objectively distant from the subject matter Subjectively engrossed in the subject matter
Nature Objective Subjective
Output Data is in the form of statistics and numbers Data is in the form of pictures and words

Source: (MacDonald and Headlam 2009).

Quantitative versus Qualitative Research

The decision of best methodology is vested in the interest of the research such that one research is best than the other. However, every method has its strengths and weaknesses, and every method is different from the other (Dawson 2009). However, a quantitative method is best suited for a large sample because a qualitative approach cannot be applied to a large sample because that will be resource and time consuming. Hence, quantitative data can be classified, calculated and specified (MacDonald and Headlam 2009).

The proposed research will be applying quantitative data because this method permits the testing of hypothesis with a large sample, which is more appropriate for answering the research questions.  However, the quantitative data is connected closely with the final part of the definition that is based on mathematically based methods (Muijs 2010). However, quantitative methods attempt to maximize replicability and objectivity. The integrity of this approach is more than qualitative research because the researcher will set aside his experiences, biases and perceptions in carrying out the study. The deductive nature of quantitative data is characterized by assuming that there is the single truth that exists which is independent of human perception and insights (Harwell 2011).  The quantitative research is quite different in purpose and execution.

  • The study is introduced based on research questions and purpose
  • The nature of the study is emphasized using theoretical perspectives and models.
  • The methodology includes evaluation of external and internal validity using sampling and experimental design respectively. Hence, statistical conclusion validity is devised using data collection and data analysis.
  •  The findings are tested by implications and discussion of the results of the proposed research.
  • The implications and conclusions are then devised supporting the theory or not (Tashakkori and Teddlie 2010).

3.3.2 Data Collection Methods       

The data collection is done using two methods.

  • Primary Data

The primary data is the direct recording of the situation and is a simple phenomenon to communicate the facts to others. The data is the original information that is collected for the first time for a specific purpose ( 2015). It is distinguished from the quality of any other data collected. However, the use of primary data can be obtained for additional study in the research (Ut 2013).

There are primarily four basic types of primary data that are differentiated from the way they are collected.

  1. Observation- The events are recorded with the help of instrument that is experienced from the researcher’s senses. The examples are a microscope, camera, tape recorder, notes, etc.
  2. Measurement- The numbers are collected indicating amounts like results, temperatures, voting polls, etc.
  3. Participation- The data is collected using the experiences of performing things rather observing such as learning to balance the time of taking questionnaires and performance. The effort is made to get the assignment done in a predetermined period.
  4. Interrogation- The data gained by investigating and asking people and understanding people’s conviction, attitude, likes and dislikes, etc. (Walliman 2010).
  5. Secondary Data

This method is assessed on the existing information that is present in various published books and journals. It differs from primary data because the actual data is not collected but still new insights can be brought into presentation or interpretation. It is used to provide the starting point for the evaluation and analysis (MacDonald and Headlam 2009).

The secondary data is headed by the details of the publication. It is majorly done from research reports, research books, scientific debates; articles replicated online, critiques of art and literary works with analysis of historical events (Dawson 2009). However, the data from secondary sources is often cross-checked for reliability and validity issues (Ríos and Del Campo 2013).

The proposed research uses primary data method for data collection because the researcher has the opinion to do a direct and indirect study about quality of the investigation. The primary data is useful and perspective as it examines the sample of the population over time and receives the exposure of experience outcomes. The primary data internal validity is experimental, controlled, managed within the study and consistent with pre-specified research practice to study the causal relationship between the variables. However, primary data collection method is valid externally because it is flexible with the criteria, systematic, constitutes a large group of observations and can apply to the other circumstances even though the results of the study can be limited (, 2016).

3.3.3 Questionnaire and Scale Method

The questionnaire method was selected as the research has made quantification possible because the research is based on positivist research paradigm and involves incorporation of descriptive and explanatory research with quantitative primary data method. Questionnaires are the most common method as it gives responses. However, it is complex and a taxing process ( 2015).  The major advantage that a questionnaire study holds that it can incorporate a large number of participant’s observation that relatively inexpensive. The data provided by questionnaire can be maintained, tabulated, organized and analyzed. On all these reasons questionnaire study is a popular method (Lammers and Badia 2013).

A questionnaire design is better than any other research method became of following reasons.

  • It can be done on a large number of participants.
  • It is easier to reach people who are scattered among the geographical spread.
  • Simple information is collected involving behaviour of the participant.

A questionnaire design is based on thought and effort that needs to be developed and planned simultaneously in some stages.

Questionnaire Design  

Source: (, 2013)

A questionnaire is restricted with two types of questions closed-ended and open-ended questions. In this research, closed-ended questions in a structured design will be used as quantitative data is chosen. However, a questionnaire design can be selected in three types namely by taking into consideration the existing questionnaires, adapt some new questionnaires or completely design a new questionnaire (, 2015).

The proposed questionnaire for this study had 23 questions with 6 independent and 1 dependent variable. The questionnaire is divided into two sections- Section A constitutes respondent’s profile with name, age, gender, marital status, the level of education, the field of work, type of hotel and income range. The questionnaire was formatted in The English language to keep it simple and understandable with a Likert scale of 5. The questionnaire was designed with a pattern of 1- strongly disagree, 2- disagree, 3- neither agree nor disagree, 4- agree and 5- strongly agree.

Nonetheless, the use of pilot testing was done to analyze the ease of the participants, the identification of the language and the time taken to complete the questionnaire (Mackey and Gass 2013). However, the early test was done using SPSS Statistical analysis tool ( 2015). The result generated gave negative results on skewness and kurtosis and the need of rephrasing the questions. Also, the second pilot test was run for the reliability analysis of the correlated factors of the independent variables. The table below depicts the descriptive statistics of 23 questions.

Descriptive Statistics

  N Mean Std.  Deviation Skewness Kurtosis
Valid Missing
Q1 199 1 4. 86 . 422 -3. 256 10. 179
Q2 199 1 4. 63 . 553 – 1. 157 . 360
Q3 199 1 4. 68 . 468 -. 770 -1. 422
Q4 199 1 4. 75 . 432 -1. 187 -. 597
Q5 199 1 4. 73 . 457 -1. 196 -. 136
Q6 199 1 4. 68 . 468 -. 770 -1. 422
Q7 199 1 4. 63 . 493 -. 684 -1. 218
Q8 199 1 4. 75 . 435 -1. 156 -. 671
Q9 199 1 4. 64 . 530 -1. 108 . 184
Q10 199 1 4. 68 . 477 -. 935 -. 762
Q11 199 1 4. 69 . 475 -. 962 -. 705
Q12 199 1 4. 82 . 382 -1. 716 . 953
Q13 199 1 4. 81 . 394 -1. 585 . 516
Q14 199 1 4. 78 . 413 -1. 390 -. 068
Q15 199 1 4. 77 . 423 -1. 285 -. 352
Q16 199 1 4. 77 . 419 -1. 319 -. 262
Q17 199 1 4. 75 . 432 -1. 187 -. 597
Q18 199 1 4. 79 . 405 -1. 465 . 147
Q19 199 1 4. 78 . 413 -1. 390 -. 068
Q20 199 1 4. 74 . 438 -1. 125 -. 742
Q21 199 1 4. 77 . 423 -1. 285 -. 352
Q22 199 1 3. 99 1. 078 -. 958 . 398
Q23 199 1 4. 77 . 434 -1. 470 . 696

The second pilot gives the reliability analysis on Cronbach’s Alpha were dependent variables are hotels and agents, and independent variable is trust, reliability, commitment, communication, liability and resources. The results were carried out using SPSS Statistical tool. The table below gives the inter-item correlation and reliability statistics for all variables.

Case Processing Summary
  N %
Cases Valid 199 99.5
Excludeda 1 .5
Total 200 100.0
Reliability Statistics
Cronbach’s Alpha Cronbach’s Alpha Based on Standardized Items N of Items
.811 .784 6
Inter-Item Correlation Matrix
  Trust Reliability Commitment Communication Loyalty Resources
Trust 1. 000 . 071 . 195 . 170 . 182 . 319
Reliability . 071 1. 000 . 180 . 097 . 037 . 035
Commitment . 195 . 180 1. 000 . 739 . 735 . 623
Communication . 170 . 097 . 739 1. 000 . 909 . 642
Loyalty . 182 . 037 . 735 . 909 1. 000 . 724
Resources . 319 . 035 . 623 . 642 . 724 1. 000

The reliability analysis measures the scale that should constantly reflect the construct. The average of these values given in the reliability analysis is estimated using Cronbach’s Alpha as the most common determinant of reliability scale. The normal alpha is measured when the score has to be summary score and standardized measure when the items are standardized before being summed. The reliability should be between 0 and 1. The convention of thumb are mentioned as _ >.9 (Excellent), _ >.8 (Good), _ >.7 (Satisfactory), _ >.6 (Debatable), _ >.5 (Poor) and _ <.5 (Unsatisfactory) (Crano et al. 2014).

Therefore, according to reliability, the overall alpha is 0.811 which is good on the reliability scale and considered good and reasonable goal for the distribution of questionnaires in data collection method for primary data. However, on the correlation matrix, the results are mixed showing an average of _>.5 poor results because the sample size is large and may bound to change with small sample size than 199 participants.

3.3.4 Target Population

The target population is the total number of participants from a population that will represent the research study. However, the target population needs to be well defined and easy to classify according to the demographic features of the participants (Neelanakavil 2015).

However, in this proposed research our target population is defined by the tourist who visits Maldives using the Ministry of Tourism in the Republic of Maldives. It is distinguished based on the field of work and type of hotel. The records are collected from Ministry of Tourism on resorts, guest houses, and hotels and are assessed on each participant from these areas as mentioned above.

3.3.5 Sampling Size and Sampling Technique

The sample size is the actual cases that are considered, and no participant was unrepresentative of the population (Wilson 2014). Hence, a total of 200 sample was taken from the Ministry of Tourism in Maldives, and 200 questionnaires were distributed to the prospective participants. However, one questionnaire went missing; that is the reason the results are based on missing data.

The sampling technique chosen was random probability sampling in which every participant has the equal probability of getting selected in the sample. This sampling had the validity of the results (Fowler 2013).

The researcher applied random sampling in choosing the tourist from the database of Tourism in Maldives and obtained the permission from the authority for the same. The questionnaires were distributed to the sample and were collected after a week while reminding the participants of the deadline for the compilation of completed questionnaire.

3.3.6 Ethics Issues and Management

Many ethical issues need to consider while writing a research from the identification of research problem to the problem generated due to results and findings. The research involves maximum moral issue when valuing the protection of the research participants. However, the purpose of the research should be clearly stated so that it does not constitute any component of deception (Jones, 2015).

Ethical considerations are thrived with data collection methods. However, proper consent should be made while informing the participants of benefits and risks for economic, social, professional, legal and physical happening. Lastly, the privacy of the participant should be maintained (Anyansi-Archibong 2015).

In this proposed research, the questionnaire was given to the participants who were willing to fill the questionnaire. However, the questionnaire was cross-checked by the Ministry of Tourism for safety purposes. A consent was signed by each voluntary participant who filled the questionnaire to protect privacy

3.3.7 Data Analysis Plan

Among the various softwares, Ms excel tools of data analysis were selected. The data helps in solving various kinds of data that are easy to use (Pallant 2013). However, it is based on point and click that helps to perform various functions. The data management is useful for large samples where multiple operations need to be performed on the same model or mixed models. The graphics are created of high quality and can be exported into any form of the document. The analysis of variance can be easily and accurately derived from Ms excel using its data analysis feature. 

In this proposed research, the data was calculated using the questionnaire. Te descriptive statistics was run on the data based on mean, kurtosis, and skewness. The researcher then runs the reliability and validity test followed by correlation and regression. After interpreting the findings, the results will be compared with the hypothesis for 6 independent variables and the dependent variable to conclude the study.

3.3.8 Research Limitations

The research limitations to carry out this study had been huge. Firstly, the target population had been restricted; the research was time-consuming and incurred huge expenses. Maldives inhabitants 80 islands and the main hub is the capital city Malè that constitutes almost one third of the locale population. Moreover, the study would have been well suited during peak periods of Maldives. However, the population being large, the sample should have been less restricted with a larger sample that could have given results that are more reliable.

Chapter 4: Result and Discussion

As discussed already the analysis of the data will be done by using the data analysis tool of MS excel, which will enable the researcher to extract the link between the collected data along with its relevancy. Moreover, a “t- Test” will be perfume on the collected data, which will be done after pairing the six independent variables with each other to make 3 pairs. The same will be done after selecting the most appropriate pair. The results of the “t- Test” performed have been highlighted below:

4.0. “t- Test” analysis

t-Test: Paired Two Sample for Means    
  Variable 1 (Trust) Variable 2(Reliability)
Mean 4.864321608 4.728643216
Variance 0.178468098 0.208821887
Observations 199 199
Pearson Correlation -0.11319222  
Hypothesized Mean Difference 0  
df 198  
t Stat 2.915425453  
P(T<=t) one-tail 0.001980714  
t Critical one-tail 1.652585784  
P(T<=t) two-tail 0.003961428  
t Critical two-tail 1.972017432  
t-Test: Paired Two Sample for Means    
  Variable 1 (Commitment) Variable 2(Loyalty)
Mean 4.64321608 4.753768844
Variance 0.281153241 0.186538754
Observations 199 199
Pearson Correlation 0.540700123  
Hypothesized Mean Difference 0  
df 198  
t Stat -3.324648432  
P(T<=t) one-tail 0.000527409  
t Critical one-tail 1.652585784  
P(T<=t) two-tail 0.001054818  
t Critical two-tail 1.972017432  
t-Test: Paired Two Sample for Means    
  Variable 1(Communication) Variable 2 (Resources)
Mean 4.809045226 4.743718593
Variance 0.155271306 0.19156388
Observations 199 199
Pearson Correlation 0.681187231  
Hypothesized Mean Difference 0  
df 198  
t Stat 2.755212845  
P(T<=t) one-tail 0.003206262  
t Critical one-tail 1.652585784  
P(T<=t) two-tail 0.006412524  
t Critical two-tail 1.972017432  

All the “t –Test” done for the six variables shows that none of these is having a P (T<=t) one-tail of more than 0.1, which clears the fact that there should not be a huge amount of variance between the collected data of these respective variables. Meanwhile, the “t –Test” also highlighted that all the variables is having P(T<=t) two-tail within the range of 0.1, which conveys another identical fact that the responses received on the independent variables will not differ from each other to any massive extent.

Dependent variable: Relationship between the Hotels and Agents in Maldives

Independent variables: The independent variables of the research are Trust, Reliability, Communication, Commitment, Resources and Loyalty.

4.1. Regression Analysis

The regression analysis in the statistical model is a certain tool which has the ability to estimate the relationship among variables and also includes various techniques for analysing and modelling several variables, when the focus is on the relationship between the one or more independent variable and one dependent variable. The regression analysis for the collected data and the dependent and independent has been highlighted below:

4.1.1. Regression analysis on TRUST

Regression Statistics                
Multiple R 0 .271107266              
R Square 0 .7349915              
Adjusted R Square 0 .5924529              
Standard Error 0 .418911938              
Observations 199              
  df SS MS F Significance F      
Regression 3 2 .714667087 0 .904889029 5 .156438582 0 .001882578      
Residual 195 34 .22000628 0 .175487212          
Total 198 36 .93467337            
  Coefficients Standard Error t Stat P -value Lower 95% Upper 95% Lower 95 .0% Upper 95 .0%
Intercept 6 .256564919 0 .44747377 13 .98197021 3 .16407E -31 5 .374055358 7 .13907448 5 .374055358 7 .13907448
Q 1  -0 .036989056 0 .088775872  -0 .416656633 0 .677387852  -0 .212073187 0 .138095075  -0 .212073187 0 .138095075
Q 2  -0 .073859218 0 .068703975  -1 .075035596 0 .283687158  -0 .209357472 0 .061639036  -0 .209357472 0 .061639036
Q 3  -0 .209695674 0 .064615018  -3 .245308592 0 .001380773  -0 .337129672  -0 .082261676  -0 .337129672  -0 .082261676

The regression analysis of the independent variable Trust shows that the R square value is quiet significant and at the same time is acceptable as well, which has been recorded at 0 .7349915 Adjusted R Square is 0 .5924529, which clears the fact that there should have been a massive connection between the various sections of collected data.

4.1.2. Regression analysis on RELIABILITY

Regression Statistics                
Multiple R 0 .692435563              
R Square 0 .479467009              
Adjusted R Square 0 .46873437              
Standard Error 0 .314804112              
Observations 199              
  df SS MS F Significance F      
Regression 4 17 .70895737 4 .427239344 44 .67372934 1 .48679E -26      
Residual 194 19 .22571599 0 .099101629          
Total 198 36 .93467337            
  Coefficients Standard Error t Stat P -value Lower 95% Upper 95% Lower 95 .0% Upper 95 .0%
Intercept 3 .686872583 0 .349768053 10 .5409072 7 .89653E -21 2 .997036425 4 .376708742 2 .997036425 4 .376708742
Q 5 0 .570342398 0 .054247999 10 .51361182 9 .49633E -21 0 .463350835 0 .677333962 0 .463350835 0 .677333962
Q 6  -0 .132402069 0 .057634027  -2 .297289892 0 .022669434  -0 .246071787  -0 .01873235  -0 .246071787  -0 .01873235
Q 7  -0 .256553598 0 .051842173  -4 .948743176 1 .61631E -06  -0 .35880023  -0 .154306966  -0 .35880023  -0 .154306966
Q 8 0 .037490902 0 .057366842 0 .653529125 0 .514189055  -0 .075651856 0 .15063366  -0 .075651856 0 .15063366

The regression analysis of the independent variable Reliability shows that the R square value is at a good position and at the same time is acceptable as well, which has been recorded at 0 .692435563 and the Adjusted R Square is 0 .479467009. This shows that the collected data do not vary from each other to any huge amount and the responses have undoubtedly highlighted the same as well.

4.1.3. Regression analysis on COMMITMENT

Regression Statistics                
Multiple R 0 .455876555              
R Square 0 .207823434              
Adjusted R Square 0 .191489896              
Standard Error 0 .388353534              
Observations 199              
  df SS MS F Significance F      
Regression 4 7 .675890642 1 .91897266 12 .72372469 3 .24508E -09      
Residual 194 29 .25878272 0 .150818468          
Total 198 36 .93467337            
  Coefficients Standard Error t Stat P -value Lower 95% Upper 95% Lower 95 .0% Upper 95 .0%
Intercept 6 .542208916 0 .360922798 18 .12633877 1 .30066E -43 5 .830372615 7 .254045217 5 .830372615 7 .254045217
Q 9  -0 .101629372 0 .069031817  -1 .472210584 0 .14258444  -0 .237778581 0 .034519837  -0 .237778581 0 .034519837
Q 10  -0 .285629522 0 .083762781  -3 .409981354 0 .000790292  -0 .450832132  -0 .120426912  -0 .450832132  -0 .120426912
Q 11  -0 .349312015 0 .079474336  -4 .395280701 1 .81992E -05  -0 .506056664  -0 .192567366  -0 .506056664  -0 .192567366
Q 12 0 .343875823 0 .123664125 2 .780724173 0 .005958366 0 .099977089 0 .587774557 0 .099977089 0 .587774557


4.1.4. Regression analysis on COMMUNICATIONS

Regression Statistics                
Multiple R 0 .285252953              
R Square 0 .81369247              
Adjusted R Square 0 .062428407              
Standard Error 0 .418202627              
Observations 199              
  df SS MS F Significance F      
Regression 4 3 .005346573 0 .751336643 4 .295968195 0 .002364364      
Residual 194 33 .92932679 0 .174893437          
Total 198 36 .93467337            
  Coefficients Standard Error t Stat P -value Lower 95% Upper 95% Lower 95 .0% Upper 95 .0%
Intercept 6 .126444561 0 .374842884 16 .34403327 2 .51519E -38 5 .387154128 6 .865734994 5 .387154128 6 .865734994
Q 13  -0 .083058783 0 .182271362  -0 .455687509 0 .649124343  -0 .442546665 0 .276429099  -0 .442546665 0 .276429099
Q 14  -0 .048471503 0 .168473264  -0 .287710356 0 .773875575  -0 .380745844 0 .283802839  -0 .380745844 0 .283802839
Q 15 0 .828206919 0 .441793496 1 .874647151 0 .062344188  -0 .04312803 1 .699541869  -0 .04312803 1 .699541869
Q 16  -0 .982630219 0 .423877043  -2 .318196362 0 .02148108  -1 .81862913  -0 .146631308  -1 .81862913  -0 .146631308

4.1.5. Regression analysis on LOYALTY

Regression Statistics                
Multiple R 0 .311215319              
R Square 0 .096854975              
Adjusted R Square 0 .082960436              
Standard Error 0 .413598136              
Observations 199              
  df SS MS F Significance F      
Regression 3 3 .577306854 1 .192435618 6 .970722506 0 .000176729      
Residual 195 33 .35736651 0 .171063418          
Total 198 36 .93467337            
  Coefficients Standard Error t Stat P -value Lower 95% Upper 95% Lower 95 .0% Upper 95 .0%
Intercept 6 .040210943 0 .350428744 17 .23663097 4 .65107E -41 5 .34909397 6 .731327916 5 .34909397 6 .731327916
Q 17 0 .084459459 0 .150129148 0 .562578689 0 .574367988  -0 .211625848 0 .380544767  -0 .211625848 0 .380544767
Q 18  -1 .060069216 0 .335026489  -3 .16413552 0 .001804663  -1 .7208098  -0 .399328631  -1 .7208098  -0 .399328631
Q 19 0 .709459459 0 .294427483 2 .40962376 0 .016898298 0 .128788397 1 .290130522 0 .128788397 1 .290130522

4.1.6. Regression analysis on RESOURCES

Regression Statistics                
Multiple R 0 .353503512              
R Square 0 .124964733              
Adjusted R Square 0 .106922769              
Standard Error 0 .408158688              
Observations 199              
  df SS MS F Significance F      
Regression 4 4 .615531593 1 .153882898 6 .926337457 3 .12223E -05      
Residual 194 32 .31914177 0 .166593514          
Total 198 36 .93467337            
  Coefficients Standard Error t Stat P -value Lower 95% Upper 95% Lower 95 .0% Upper 95 .0%
Intercept 6 .179635344 0 .351363847 17 .58756742 5 .00597E -42 5 .486651852 6 .872618835 5 .486651852 6 .872618835
Q 20  -0 .292253023 0 .140964464  -2 .073238985 0 .039471203  -0 .570272652  -0 .014233393  -0 .570272652  -0 .014233393
Q 21  -0 .187598841 0 .166307853  -1 .128021542 0 .26070393  -0 .515602412 0 .14040473  -0 .515602412 0 .14040473
Q 22  -0 .091995 0 .027640279  -3 .328294893 0 .001045488  -0 .146509024  -0 .037480976  -0 .146509024  -0 .037480976
Q 23 0 .2562853 0 .16077996 1 .594012719 0 .112561076  -0 .060815786 0 .573386387  -0 .060815786 0 .573386387

The Multiple R and the R square of all the regression analysis was not more less than 0.1 which is a great sign for accepting the fact that the data collected are quiet relevant can be kept for future reference as well. Moreover, the R square have increase to 0.6 in some cases which shows that those questions ha huge positive responses, one of which is the independent variable of communication that was recorded at 0.8. Therefore, it can be quiet reasonably said that the communication is one of the most pivotal element that will enable the Hotel and the agents of the tourism sector of Maldives to create a standard level of understanding within each other.

As per the huge positive results achieved from the regression analysis of the independent variable “communication”, further studies have been done on this segment. The researcher will analyse the data that is collected from the respondents for the questions of 13, 14, 15 and 16. The detailed analysis of the independent variable of communication will be done by residual output and probability output, which has been shown below:

The above table and graphs shows that all the responses receive from the residuals from all the 199 respondents are at par and near the standard residuals, which justifies the fact that communication is one of the major element among all that needs to happen in a free flowing manner within the Hotels and the agents within the tourism sector of Maldives.

5.0. Descriptive Statistics

5.1. Descriptive Statistics (Trust)

Q 1   Q 2   Q 3   Q 4  
Mean 4. 864321608 Mean 4. 628140704 Mean 4. 67839196 Mean 4. 753768844
Standard Error 0. 02994703 Standard Error 0. 039179187 Standard Error 0. 033194887 Standard Error 0. 030616673
Median 5 Median 5 Median 5 Median 5
Mode 5 Mode 5 Mode 5 Mode 5
Standard Deviation 0. 422454847 Standard Deviation 0. 552690445 Standard Deviation 0. 468271512 Standard Deviation 0. 431901325
Sample Variance 0. 178468098 Sample Variance 0. 305466728 Sample Variance 0. 219278209 Sample Variance 0. 186538754
Kurtosis 10. 17913437 Kurtosis 0. 360264452 Kurtosis -1. 422029853 Kurtosis -0. 597003786
Skewness -3. 256144153 Skewness -1. 157209668 Skewness -0. 769651969 Skewness -1. 187054371
Range 2 Range 2 Range 1 Range 1
Minimum 3 Minimum 3 Minimum 4 Minimum 4
Maximum 5 Maximum 5 Maximum 5 Maximum 5
Sum 968 Sum 921 Sum 931 Sum 946
Count 199 Count 199 Count 199 Count 199
Largest(1) 5 Largest(1) 5 Largest(1) 5 Largest(1) 5
Smallest(1) 3 Smallest(1) 3 Smallest(1) 4 Smallest(1) 4
Confidence Level(95. 0%) 0. 059056065 Confidence Level(95. 0%) 0. 077262039 Confidence Level(95. 0%) 0. 065460897 Confidence Level(95. 0%) 0. 060376613


The descriptive statistics of the independent variable trust (Question 1) shows highlights various sections; one of the major among them is the mean and standard deviation which are 4.86 and 0.422 respectively. Moreover, the second question in the same segment shows a mean of 4.62 and SD of 0.55, which are quiet balanced and acceptable. Identical elements are applicable for the next two questions as well.

5.2. Descriptive Statistics (Reliability)

Q 5   Q 6   Q 7   Q 8  
Mean 4.728643216 Mean 4.67839196 Mean 4.633165829 Mean 4.748743719
Standard Error 0.032393768 Standard Error 0.033194887 Standard Error 0.034983193 Standard Error 0.030824246
Median 5 Median 5 Median 5 Median 5
Mode 5 Mode 5 Mode 5 Mode 5
Standard Deviation 0.456970335 Standard Deviation 0.468271512 Standard Deviation 0.49349867 Standard Deviation 0.434829503
Sample Variance 0.208821887 Sample Variance 0.219278209 Sample Variance 0.243540937 Sample Variance 0.189076697
Kurtosis -0.135597666 Kurtosis -1.422029853 Kurtosis -1.218162518 Kurtosis -0.671175008
Skewness -1.195689769 Skewness -0.769651969 Skewness -0.683810902 Skewness -1.155712912
Range 2 Range 1 Range 2 Range 1
Minimum 3 Minimum 4 Minimum 3 Minimum 4
Maximum 5 Maximum 5 Maximum 5 Maximum 5
Sum 941 Sum 931 Sum 922 Sum 945
Count 199 Count 199 Count 199 Count 199
Largest(1) 5 Largest(1) 5 Largest(1) 5 Largest(1) 5
Smallest(1) 3 Smallest(1) 4 Smallest(1) 3 Smallest(1) 4
Confidence Level(95.0%) 0.063881076 Confidence Level(95.0%) 0.065460897 Confidence Level(95.0%) 0.068987467 Confidence Level(95.0%) 0.060785951

5.3. Descriptive Statistics (Commitment)

Q 9   Q 10   Q 11   Q 12  
Mean 4.64321608 Mean 4.683417085 Mean 4.688442211 Mean 4.824121
Standard Error 0.037587636 Standard Error 0.033815335 Standard Error 0.0336755 Standard Error 0.027056
Median 5 Median 5 Median 5 Median 5
Mode 5 Mode 5 Mode 5 Mode 5
Standard Deviation 0.530238853 Standard Deviation 0.477024005 Standard Deviation 0.475051391 Standard Deviation 0.381678
Sample Variance 0.281153241 Sample Variance 0.227551901 Sample Variance 0.225673824 Sample Variance 0.145678
Kurtosis 0.184397243 Kurtosis -0.762362756 Kurtosis -0.704619369 Kurtosis 0.952903
Skewness -1.108022321 Skewness -0.935055184 Skewness -0.962109495 Skewness -1.71564
Range 2 Range 2 Range 2 Range 1
Minimum 3 Minimum 3 Minimum 3 Minimum 4
Maximum 5 Maximum 5 Maximum 5 Maximum 5
Sum 924 Sum 932 Sum 933 Sum 960
Count 199 Count 199 Count 199 Count 199
Largest(1) 5 Largest(1) 5 Largest(1) 5 Largest(1) 5
Smallest(1) 3 Smallest(1) 3 Smallest(1) 3 Smallest(1) 4
Confidence Level(95.0%) 0.074123473 Confidence Level(95.0%) 0.06668443 Confidence Level(95.0%) 0.066408673 Confidence Level(95.0%) 0.053356

5.4. Descriptive Statistics (Communication)

Q 13   Q 14   Q 15   Q 16  
Mean 4.809045226 Mean 4.783919598 Mean 4.768844221 Mean 4.773869347
Standard Error 0.027933095 Standard Error 0.029248989 Standard Error 0.029959803 Standard Error 0.029729044
Median 5 Median 5 Median 5 Median 5
Mode 5 Mode 5 Mode 5 Mode 5
Standard Deviation 0.394044802 Standard Deviation 0.412607762 Standard Deviation 0.422635037 Standard Deviation 0.419379777
Sample Variance 0.155271306 Sample Variance 0.170245165 Sample Variance 0.178620375 Sample Variance 0.175879397
Kurtosis 0.515734259 Kurtosis -0.068152365 Kurtosis -0.352042737 Kurtosis -0.262109485
Skewness -1.58450379 Skewness -1.390192124 Skewness -1.285144771 Skewness -1.319328025
Range 1 Range 1 Range 1 Range 1
Minimum 4 Minimum 4 Minimum 4 Minimum 4
Maximum 5 Maximum 5 Maximum 5 Maximum 5
Sum 957 Sum 952 Sum 949 Sum 950
Count 199 Count 199 Count 199 Count 199
Largest(1) 5 Largest(1) 5 Largest(1) 5 Largest(1) 5
Smallest(1) 4 Smallest(1) 4 Smallest(1) 4 Smallest(1) 4
Confidence Level(95.0%) 0.055084551 Confidence Level(95.0%) 0.057679516 Confidence Level(95.0%) 0.059081255 Confidence Level(95.0%) 0.058626193

5.5. Descriptive Statistics (Loyalty)

Q 17   Q 18   Q 19  
Mean 4.753768844 Mean 4.793969849 Mean 4.783919598
Standard Error 0.030616673 Standard Error 0.028743179 Standard Error 0.029248989
Median 5 Median 5 Median 5
Mode 5 Mode 5 Mode 5
Standard Deviation 0.431901325 Standard Deviation 0.405472438 Standard Deviation 0.412607762
Sample Variance 0.186538754 Sample Variance 0.164407898 Sample Variance 0.170245165
Kurtosis -0.597003786 Kurtosis 0.146815172 Kurtosis -0.068152365
Skewness -1.187054371 Skewness -1.46473243 Skewness -1.390192124
Range 1 Range 1 Range 1
Minimum 4 Minimum 4 Minimum 4
Maximum 5 Maximum 5 Maximum 5
Sum 946 Sum 954 Sum 952
Count 199 Count 199 Count 199
Largest(1) 5 Largest(1) 5 Largest(1) 5
Smallest(1) 4 Smallest(1) 4 Smallest(1) 4
Confidence Level(95.0%) 0.060376613 Confidence Level(95.0%) 0.05668205 Confidence Level(95.0%) 0.057679516

5.6. Descriptive Statistics (Resources)

Q 20   Q 21   Q 22   Q 23  
Mean 4.743718593 Mean 4.768844221 Mean 3.989949749 Mean 4.768844221
Standard Error 0.03102632 Standard Error 0.029959803 Standard Error 0.076398671 Standard Error 0.03079527
Median 5 Median 5 Median 4 Median 5
Mode 5 Mode 5 Mode 5 Mode 5
Standard Deviation 0.437680112 Standard Deviation 0.422635037 Standard Deviation 1.077735888 Standard Deviation 0.434420746
Sample Variance 0.19156388 Sample Variance 0.178620375 Sample Variance 1.161514644 Sample Variance 0.188721385
Kurtosis -0.74195605 Kurtosis -0.352042737 Kurtosis 0.397590416 Kurtosis 0.696471369
Skewness -1.124990087 Skewness -1.285144771 Skewness -0.958018609 Skewness -1.470424543
Range 1 Range 1 Range 4 Range 2
Minimum 4 Minimum 4 Minimum 1 Minimum 3
Maximum 5 Maximum 5 Maximum 5 Maximum 5
Sum 944 Sum 949 Sum 794 Sum 949
Count 199 Count 199 Count 199 Count 199
Largest(1) 5 Largest(1) 5 Largest(1) 5 Largest(1) 5
Smallest(1) 4 Smallest(1) 4 Smallest(1) 1 Smallest(1) 3
Confidence Level(95.0%) 0.061184445 Confidence Level(95.0%) 0.059081255 Confidence Level(95.0%) 0.150659512 Confidence Level(95.0%) 0.06072881


From above tables it can be clearly seen that all the independent variables, which have three to four questions each can be evaluate for the discussion. These elements play a massive role in the present time to affect the relationship within the Hotels and the agents. All of the variables along with each of the questions are having a standard mean and the standard deviation is within 1.0, which shows the positive nature the data. Moreover, the sample variance have not crossed the mark of 1.1 in any of these sections, which shows the very minimum amount of variance that has been found within the whole collected data. The Kurtosis has remained within the range of 1.2, which can be highlighted as an average response, though some questions have exceeded the said amount marginally. Meanwhile, the Skewness have remained within the range of 2.0, which states that the responses in almost all sections was quiet positive, hence proving all the hypothesis to be correct.

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Chapter 5: Conclusion and Recommendation

The main purpose of the research is to analyse the factors that affect the relationship between the agents and hotels operating in the tourism sector of Maldives, which have not been great in the recent past. After conducting the entire research some of the major conclusion that has been found has been highlighted below.

The first and foremost element that can be highlighted is regarding the independent variable “communication”. There were huge positive responses within this section of communication between the hotels and the agents, which clears the fact that communication plays a massive role in clearing out minor and major doubts and at the same time also strengthens the business relationship to quiet some extent. Moreover, another pivotal element that has been extracted from the research and can be highlighted as a major conclusion is regarding the hotels and agents running their business in a smooth manner. However the process has got even smother due to the recent rush of tourists in Maldives.

In the recent epoch various researchers have noted down the fact that Hotels and Agents of the Maldives tourism industry have tied up with each other in order to increase their individual revenue by serving even more tourists at a single time. This relationship can be termed a business relation that already had various significant changes on the business operations of the both Hotels and Agents of the Maldives tourism industry.

The recent time is witnessing Maldives as an ideal place for attracting tourists but, previously the scenario was completely different, as tourism development was immensely private sector- driven and has always been a debate topic of whether previous tourism masterplans always had a profound significance on the directions of growth and opulence. Meanwhile, it is of much importance to note that all the six independent variables of the research have been found to be positive and hence neglecting may result negatively in the relationship between the hotels and agents operating in the tourism sector of Maldives.

Implications for Practice and Recommendations

For creating a successful business in today’s marketplace, a strong relationship bond between clients, business and its agents should be created. When taking the hotel business into account, agents are playing an important role-play. Therefore, it is vital for the hotel business owners to create a strong and long-lasting relationship with their loyal agents. To do that, hotel business owners take the help of B2B relationship available today in the marketing strategy. Hence, the fact is proved that communication is one of the elements that uphold the relationship between the agents and hotels. Both the parties are recommended to act together and prepare a certain communication strategy or process, which will break down all communication barriers among them. 

Building this type of strategy or communication process will end various types of issues among the hotels and agents, hence augmenting their business relationship for the next venture. Moreover, this will also build trust which will help in future ventures among both the parties as well. Another massive recommendation that can be put forward is regarding the loyalty factor, within which it can be recommended to both the parties that they should b loyal to each other despite of any rise or fall in profit proportions in any particular assignment. This will establish a strong bonding within the two, which later will enable both the parties to work together in critical situations, thus extracting profit from even in tough times such as off seasons.

Scope of Future Research

Though the research have covered all possible sections and is conducted only in Maldives, the future researchers are recommended to explore various other locations as well. Meanwhile, the most probable future condition of the tourism industry in Maldives and other nations can be explored as well.  However, further research on the tourism sector of Maldives is possible, but at the same time the factors and the independent variables should be selected diversely and minutely in order to achieve valuable findings and propagate the same as well.


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